Storing and Retrieving Bicycle Location Data via REST API
Design scalable and loosely coupled architectures.
Design highly available and/or fault-tolerant architectures.
Determine high-performing database solutions.
Answer
Correct answer: B — Use Amazon API Gateway with AWS Lambda to receive bicycle location data through a REST API, process it serverlessly, and store it for access by the existing analytics platform.
A bicycle sharing company is developing a multi-tier architecture to track the location of its bicycles during peak operating hours. The company wants to use these data points in its existing analytics platform. A solutions architect must determine the most viable multi-tier option to support this architecture. The data points must be accessible from the REST API. Which action meets these requirements for storing and retrieving location data?
Community Insight
The question tests whether you can identify a multi-tier pattern that provides REST API access while also handling data storage and processing — the trap is assuming Kinesis Data Analytics can be directly wired to API Gateway, when it actually requires Kinesis Data Streams as an input source.
This SAA-C03 scenario requires a multi-tier serverless architecture where bicycle location data is stored and exposed through a REST API for consumption by an existing analytics platform. Amazon API Gateway combined with AWS Lambda satisfies both the REST API access requirement and the data processing/storage need, making option B the correct choice.
Many learners select D (API Gateway with Kinesis Data Analytics) because Kinesis seems more suited to high-volume telemetry, but Kinesis Data Analytics cannot accept API Gateway as a direct input — it requires Kinesis Data Streams or Firehose as the ingestion layer, which is not mentioned in the option.
Community Discussion (173 comments)
slogans
👍 1
Selected: B
B is correct ❌ D — API Gateway + Kinesis Data Analytics real-time stream processing / analytics It isn't the normal storage/retrieval layer for an application's REST API.
Cert_Portal
👍 1
Selected: D
Why D is correct: API Gateway provides the REST API layer — bikes (or the mobile app) send location updates via REST, and the data can be queried via REST Kinesis Data Analytics is purpose-built to process and analyze streaming data in real time (using SQL or Apache Flink). Continuous location pings are the textbook streaming use case API Gateway can act as a direct proxy into the Kinesis family, so the tiers connect natively
Satheeshsivan
👍 1
Selected: D
Amazon API Gateway + Amazon Kinesis Data Analytics is the right combination for this use case because it addresses both the real-time streaming nature of bicycle location data and the REST API accessibility requirement.
Tim2026
👍 1
Selected: B
You need a REST API + real-time processing of location data → API Gateway exposes the REST endpoints, Lambda handles ingestion/logic.
TEC65
👍 1
Selected: D
better for streaming data
Vivobook11
👍 2
Selected: D
D. Use Amazon API Gateway with Amazon Kinesis Data Analytics. Why? Real-time Data Processing: Amazon Kinesis Data Analytics can process streaming data (e.g., bicycle locations) in real-time. REST API Access: Amazon API Gateway can provide a secure REST API for accessing the processed data. Scalability & Performance: Kinesis efficiently ingests large volumes of data during peak hours. Integration with Analytics: The processed data can be stored in Amazon S3, DynamoDB, or Redshift for further analytics.
Faraz999
👍 2
Selected: B
API Gateway is needed to get the data so option A and C are out. “The company wants to use these data points in its existing analytics platform” so there is no need to add Kynesis. Option D is also out. This leaves us with option B as the correct one.
CloudExpert01
👍 2
Selected: B
when choosing between B and D: "The company wants to use these data points in its existing analytics platform." so need for Lambda to integrate data points in its existing analytics platform
Saloniip
👍 2
Selected: B
lambda can store data in db which is not mentioned but can be implemented, wherein kinesis data analytics would be more complex to implement just for simple location tracking. Also, a data analytics tool is already there. Hence, B is more suitable.
tch
👍 1
Selected: D
Amazon Kinesis Data Analytics allows you to build more complex analytics applications that support flexible processing choices and robust fault-tolerance with exactly-once processing without duplicates, and analytics that can be performed over an entire data stream across multiple logical partitions. With KDA, you can analyze data over multiple types of aggregation windows (tumbling window, stagger window, sliding window, session window) using either the event time or the processing tim
zdi561
👍 1
Selected: D
Lambda is not most viable, or real time
FlyingHawk
👍 3
Selected: B
Given that the company already has an existing analytics platform and needs a solution for storing and retrieving location data that can be accessed through a REST API, the best choice is: B. Use Amazon API Gateway with AWS Lambda
FlyingHawk
👍 1
D. Amazon API Gateway with Amazon Kinesis Data Analytics: Kinesis Data Analytics is for continuous real-time stream processing. If the requirement focuses only on storing and retrieving (not streaming) data, this adds unnecessary complexity.
FlyingHawk
👍 3
Selected: D
Kinesis is specifically designed for telemetry data, making it a better fit for tracking bicycle locations.
FlyingHawk
👍 1
I changed my mind to B now as there is existing analytic platform already, the data will be stored in the existing analytic platform, so you can use Lambda to process and store data in the existing analytic platform.
Rcosmos
👍 2
Selected: D
B. Amazon API Gateway com AWS Lambda: Essa combinação é útil para fornecer APIs REST, mas o Lambda não é otimizado para ingestão contínua de dados de localização em tempo real. Ele seria mais adequado para processos eventuais ou tarefas específicas.
hashepsut
👍 1
Selected: B
the best answer is B: Use Amazon API Gateway with AWS Lambda Reasoning: API Gateway provides the required REST API endpoint Lambda can handle real-time processing of location data This combination is cost-effective and scalable Can easily integrate with other AWS services for analytics Provides the necessary multi-tier architecture (API Layer, Processing Layer, Storage Layer)
EllenLiu
👍 1
Selected: D
A common use is the real-time aggregation of data followed by loading the aggregate data into a data warehouse or map-reduce cluster. https://docs.aws.amazon.com/streams/latest/dev/introduction.html#using-the-service
kimm_10
👍 1
Selected: D
D is the most viable multi-tier option, as it supports real-time data ingestion, analytics, and accessibility through a REST API.
PSH123
👍 1
Selected: B
kinesis more complex than lambda
0de7d1b
👍 1
Selected: D
The company needs to track bicycle locations during peak operating hours and make this data accessible via a REST API. The data will be part of an analytics platform, so the solution should support real-time data processing, storage, and easy retrieval. Amazon API Gateway: This can be used to create a REST API to receive and expose the location data of the bicycles. Amazon Kinesis Data Analytics: This service is specifically designed to process real-time streaming data, such as location data points sent from the bicycles. It enables real-time analytics and can seamlessly integrate with other services like Amazon S3, DynamoDB, or Amazon Redshift, which may be used for further storage or analysis.
jayessh
👍 1
Selected: B
According to copilot: Initial setup & scaling ability of lambda is way better than kinesis. Also for storing data points we need DB or any other solution in both cases, which should not be point for considering answer here
Sergantus
👍 3
Selected: D
API Gateway is definitely needed, so A and C are out, I would agree with B is there was SQS in the picture, as Lambda may not be able to work with a large volume of continuous location data.
Mish
👍 1
D. Use Amazon API Gateway with Amazon Kinesis Data Analytics.
Omariox
👍 2
Selected: D
it should be D because ChatGPT said that :D
PaPi_z
👍 3
Selected: D
The most viable option for storing and retrieving location data in a multi-tier architecture with the requirements mentioned is D. Use Amazon API Gateway with Amazon Kinesis Data Analytics. Here's why: Amazon API Gateway: It provides a managed solution for exposing a REST API, which is needed for making the location data accessible to external clients and applications. Amazon Kinesis Data Analytics: This service is designed to handle real-time data streams and analytics, which is ideal for tracking the location of bicycles during peak operating hours when real-time data processing is essential. Kinesis Data Analytics can efficiently process, analyze, and store the location data from bicycles, making it a good fit for real-time tracking scenarios. This solution supports the real-time ingestion of location data and enables integration with the company's existing analytics platform for further processing, while also providing access to the data via REST APIs.
PaPi_z
👍 2
continues here... Why the other options are less viable: A. Use Amazon Athena with Amazon S3: While Athena is great for querying large datasets stored in S3, it is not suitable for real-time data processing and tracking since it is more focused on batch querying rather than continuously ingesting and processing live data streams. B. Use Amazon API Gateway with AWS Lambda: While this combination is useful for building scalable APIs, AWS Lambda is not designed for high-throughput real-time data processing or storage of continuous data streams. It would be complex and inefficient for storing and analyzing real-time location data from the bikes. C. Use Amazon QuickSight with Amazon Redshift: QuickSight is primarily a data visualization tool, and Redshift is used for data warehousing and batch processing. This combination is not suitable for handling real-time streaming data and making it accessible via a REST API.
PaulGa
👍 3
Selected: D
Ans D - hint: "The data points must be accessible from the REST API" so we need an API interface - that's leaves only B or D, of which B uses a Lambda function (undefined) and D provides Kinesis data analytics
tomasiraz
👍 4
Kinesis data analytics cant consume from API Gateway, only from Kinesis Data Stream or Amazon Data Firehose https://docs.aws.amazon.com/es_es/kinesisanalytics/latest/dev/what-is.html
SaurabhTiwari1
👍 3
Selected: B
B seems right, because it has already existing analytics plateform so don't need D.
rpmaws
👍 1
Selected: D
In option B who will ingest realtime data in S3 ? so Answer is D.
bignatov
👍 3
Selected: D
RDS Event Notification: Amazon RDS supports event notifications, which can trigger actions when specific events occur, such as a record update or delete operation. In this case, an event would be triggered when a listing is removed. Amazon SNS: SNS allows the event to be published to a topic that can then be fanned out to multiple SQS queues. This is useful when you have multiple target systems that need to receive the data. SNS can push the message to all subscribed SQS queues simultaneously. Amazon SQS: SQS provides reliable message queuing. Each target system can consume messages from its respective SQS queue at its own pace, ensuring that no messages are lost. AWS Lambda: Lambda functions can be triggered by the SQS queues to process the messages and update the target systems accordingly. This approach allows for asynchronous processing and decouples the RDS update from the target system updates, improving scalability and reliability.
knben
👍 2
Selected: D
D is the correct answer!
KTEgghead
👍 1
Selected: B
To meet the requirements for storing and retrieving location data in a multi-tier architecture with accessibility from a REST API, the most viable option would be to use Amazon API Gateway with AWS Lambda. This combination allows for the creation of a serverless architecture that can handle the data points effectively: Amazon API Gateway: Acts as the front door for the REST API, managing and securing the traffic to the back-end services. AWS Lambda: Processes the incoming requests from the API Gateway, performs operations such as storing and retrieving location data, and integrates with other AWS services as needed. This setup enables the bicycle sharing company to have a scalable, cost-effective, and efficient system for tracking the location of its bicycles and integrating the data with its existing analytics platform.
jaradat02
👍 1
Selected: B
All of these options are a little bit vague, we can rule out A and C because they don't provide a solution for the API requirement, since the company has it's own analytics platform, we can rule out D, although option B doesn't provide a storage solution, it's the one that makes the most sense.
jatric
👍 1
Selected: A
Option A makes more sense as this provide both storing option as S3 and rest endpoint in Athena to retrieve data points integrating with S3
ChymKuBoy
👍 1
Selected: B
B for sure
JunsK1e
👍 2
Selected: D
you can't store data in lambda
HeliosABC
👍 4
Selected: D
Track location, it should be streaming
MomenAWS
👍 1
Selected: D
D is more reasonable than B
Solomon2001
👍 1
Selected: D
https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway.html
professorx123
👍 2
Selected: D
Amazon API Gateway with Amazon Kinesis Data Analytics is used for processing and analyzing streaming data in real-time using SQL or Apache Flink. While it's suitable for real-time analytics, it's not typically used for storing and retrieving data in a RESTful API format.
Tralfalgarlaw
👍 2
Selected: B
The company wants to use these data points in its existing analytics platform We don't need analytics platform, B. The correct answer
f761d0e
👍 2
B. The q states that they already have an analytics platform, I thought D but that would be changing the platforms.
MehulKapadia
👍 5
Selected: D
Keyword: "Accessible from the REST API". So option A and C are not correct Option. Remaining Options B and D. Option B is not a correct answer because After API Gateway to Lambda Function, what next ?. where will data go ?. but with Option D API Gateway with Kenesis Data Stream you have an option of sending data(through Firehose) to third party partner destination like DataDog, NewRelic, MongoDB, Splunk etc. Correct Answer D
zinabu
👍 1
selected answer: D kinesis can store the data for analysis.
HarryLopez
👍 2
We need API Gateway for rest apis, so A and C are out. Among B and D, there is an existing analytics platform so no need for Kinesis. Also, Kinesis Data Analytics relies on data source: either Kinesis Data Firehose or Kinesis Data Streams. It cannot work directly with API Gateway, so option D) is out. That leaves B).
danwantstolearn
👍 1
Selected: D
D because B mentions no way to store data.
farnamjam
👍 4
Selected: B
Comparison to other options: A. Athena and S3: While storing data in S3 and querying it with Athena is cost-effective, it wouldn't provide real-time data access needed for the API. C. QuickSight and Redshift: QuickSight and Redshift are excellent for analytics, but wouldn't directly expose data through the API. You'd still need a Lambda function to act as an intermediary. D. API Gateway and Kinesis Data Analytics: Kinesis Data Analytics is suitable for real-time streaming analysis, but it wouldn't directly provide a REST API endpoint. You'd need additional setup like API Gateway or Lambda for API access.
rvca231
👍 7
Selected: B
Kinesis Data Analytics requires a Kinesis Data Streams or Kinesis Data Firehose as input streams, so you cannot directly connect it to API Gateway, therefore B is the answer
awsgeek75
👍 3
Selected: D
A: Athena on S3 is query B: API + Lambda is just API C: Analytics and reporting D: API and analytics with storage D is the correct answer
pdragon1981
👍 2
Selected: D
I would go for option D, use of gateway API is needed and also is necessary to store the data so the unique option available is D, lambda can´t store data
data_cloud_aws
👍 2
Selected: D
Keywords : API , Storing D
SaurabhTiwari1
👍 2
Selected: B
B is correct B. Use Amazon API Gateway with AWS Lambda. This option allows the company to create, deploy, and manage a RESTful API to expose the required endpoints. AWS Lambda can be used to process the incoming requests and perform CRUD operations. The processed data can then be stored in a database like Amazon DynamoDB. This architecture would be serverless, scalable, and cost-effective. It would also allow real-time tracking of bicycles during peak operating hours. The other options do not provide the same level of real-time processing and flexibility for this specific use case.
pentium75
👍 1
"The processed data can then be stored in a database like Amazon DynamoDB" -> but B does not mention a database, though 'storing data' is part of the requirement.
xdkonorek2
👍 3
Selected: A
I'm going with A https://docs.aws.amazon.com/athena/latest/ug/what-is.html "Athena helps you analyze unstructured, semi-structured, and structured data stored in Amazon S3." It provides REST API for interacting with it https://docs.aws.amazon.com/athena/latest/APIReference/API_Operations.html you can access data points via sql queries B: doesn't mention how data will be stored C: QuickSight don't provide api for accessing data points from data sources D: you can integrate API Gateway with Amazon Kinesis but it's very limited API, I don't see a posiblity to read a data point from it https://docs.aws.amazon.com/kinesisanalytics/latest/dev/API_Operations.html
pentium75
👍 2
"Athena helps you analyze" .. But we don't want to analyze. We want to retrieve and store the data and make it available to an existing analytics platform via REST API.
slimen
👍 1
Selected: B
the do have an analytic platform, adding kenises = more money + more operational overhead
pentium75
👍 1
Nothing is SENT via API GW, the stem tells us that they want to RETRIEVE the stored data via REST API (= API GW). The "existing analytic platform" will use this REST API; Lambda will not "send" anything there.
ZZNZ
👍 1
Selected: B
"The company wants to use these data points in its existing analytics platform"
tom_cruise
👍 1
Selected: D
If you choose the lambda function, where does it pull data from?
slimen
👍 1
the data is being sent to API gateway using REST API GW will send data to Lambda Lambda wills end data to the existing analytic platform they have an analytic platform already, Kenises is not needed
M0SHE
👍 3
Selected: D
Using Amazon API Gateway with AWS Lambda: This combination allows for creating a serverless REST API. AWS Lambda can process the data, but it doesn't inherently store it. It would need an additional data storage service. Using Amazon API Gateway with Amazon Kinesis Data Analytics: This combination allows for real-time analysis of streaming data, and the data can be exposed via a REST API using Amazon API Gateway. Amazon Kinesis Data Analytics can process and analyze the streaming data in real-time, making it a suitable choice for the scenario described. Moreover, Amazon Kinesis Data Analytics can ingest data and not only store the data points but can expose them as REST API, which aligns with the requirements of the scenario1.
Ramdi1
👍 1
Selected: D
i think the answer is D because of the storing data requirement
vijaykamal
👍 1
Selected: D
lambda does not store the information and since real time tracking is needed for peak hrs., kinesis would work better
rushiwaman95
👍 1
tracking = real time
chandu7024
👍 1
It should be D.
pentium75
👍 1
What, Kinesis cannot retrieve data?
kambarami
👍 2
Answer is D. Amazon Kinesis Data Streams is a serverless streaming data service that simplifies the capture, processing, and storage of data streams at any scale. Kinesis Data Firehose.
sonyaws
👍 1
Selected: B
Correction required in question: Which action meets these requirements for sorting(*not storing) and retrieving location data? - Lambda function does the sorting and retrieving - API Gateway exposes a RestAPI to call the Lambda function
Stevey
👍 3
Selected: D
D because a storage solution is required. B. Lamda is not a storage solution.
karloscetina007
👍 2
Selected: D
D is the correct answer. Lambda can not store the infotmation for analysis, instead API gateway and Kinesis could do that years ago.
Guru4Cloud
👍 3
Selected: D
The best option is to use Amazon API Gateway with Amazon Kinesis Data Analytics. Amazon API Gateway provides a REST API that can be used to ingest and retrieve the location data points. Kinesis Data Analytics can then process and analyze those data streams in real-time. The results can be queried through the API Gateway, meeting the requirements.
ack1
👍 2
Selected: D
D is right answer
oeufmeister
👍 1
Selected: D
Kinesis will probably do the job better
RupeC
👍 2
Selected: D
The last line of the question states: "for storing and retrieving location data?" Thus as B has no storage capability unless you add DynamoDB which is out of scope. D is the only answer that fulfils the brief. Reading the other answers, I think B is more elegant and has less redundancy given the existing dev but you would have to address the storage.
MutiverseAgent
👍 5
Also by using kinesis the analytics platform will have a storing buffer to take & process data through the kinesys API. The lambda aproach in the B scenario is to wide and leaves many loose ends.
FlyingHawk
👍 2
AWS Lambda provides a serverless way to process incoming requests and interact with a storage backend. This solution can store location data in a service like Amazon DynamoDB or Amazon S3 and use Lambda functions to retrieve and serve this data through the API Gateway. This is cost-effective, scalable, and straightforward for real-time queries.
Aash24
👍 2
Selected: D
D should be
small_zipgeniuis
👍 7
Selected: B
B is correct. With D option API Gateway cannot connect directly to Kinesis Data Analitics. If this would be Kinesis Data Streams this would be feasible
aadityaravi8
👍 2
D should be right answer. Using Amazon API Gateway with Amazon Kinesis Data Analytics allows you to capture and process streaming data in real-time. This architecture provides the ability to capture and analyze location data in real-time, allowing the bicycle sharing company to track the location of its bicycles during peak operating hours. The REST API exposed through Amazon API Gateway enables easy access to the location data. Option B, using Amazon API Gateway with AWS Lambda, can be a valid choice for handling REST API requests, but it may not be the optimal solution for real-time data processing and analytics.
cookieMr
👍 4
Selected: B
Combination of API Gateway and Lambda provides a scalable and cost-effective solution for handling the REST API and processing the location data. API Gateway can handle the API request and response management, while Lambda can process and store/retrieve the location data from a suitable data store like Amazon S3. Options A, C, and D are not the most suitable options for storing and retrieving location data in this scenario: Option A suggests using Amazon Athena with Amazon S3, which is a query service for data in S3 but does not provide a direct REST API integration for real-time location data retrieval. Option C suggests using Amazon QuickSight with Amazon Redshift, which is more suitable for data analytics and visualization rather than real-time data retrieval through a REST API. Option D suggests using Amazon API Gateway with Amazon Kinesis Data Analytics, which is more suitable for real-time streaming analytics rather than data storage and retrieval for REST APIs.
Abobaloyi
👍 1
Selected: D
" track the location of its bicycles during peak operating hours" Amazon Kinesis Data Analytics is the easiest way to transform and analyze streaming data in real time.
Bmarodi
👍 1
Selected: D
The option D is correct answer.
Abrar2022
👍 1
Kinesis Data Analytics as the name suggests is for analytics not storing. Lambda isn't storing the data themselves. It's triggering the data store to the company's "existing data analytics platform"
Bmarodi
👍 1
Selected: D
The key words here are: existing analytics platform Kinesis, and The data points must be accessible from the REST API, hence the right answer is option D.
Futurebones
👍 1
Selected: A
I would go for A. as no other answers have showed satisfactory solutions for storing data. Even the question hasn’t been explicit with the size of the number. Considering it’s a bicycle sharing company, the location data generated everyday can be a huge number.
bgsanata
👍 1
Selected: D
Between C and D, the correct one is D. Kinesis analytics output to S3, RedShift, Elasticsearch and Kinesis Data Streams. Lambda require additional logic to get the data stored somewhere.
pbpally
👍 1
Selected: D
It's stuck between B and D but the giveaway is needing to store. KDA can store, Lambda cannot.
Konb
👍 3
Selected: B
Given API is needed it's B or D Given an existing analytics platform - what the solution needs to do is basically provide some querying to this existing platform. Therefore B
shinejh0528
👍 1
Selected: B
Just remember this keyworkd : API GW
kruasan
👍 3
Selected: B
Data points in its existing analytics platform + Data points must be accessible from the REST API + Track the location of its bicycles during peak operating hours They already have an analytics platform, A (Athena) and D (Kinesis Data Analytics) are out of the race even though S3 & APT Gateway Support REST API. Now B and C are in Race. C will not support REST API. So the answer should be B
Heric
👍 1
Selected: B
Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. Using Amazon API Gateway with AWS Lambda enables the bicycle sharing company to easily create a REST API that can receive location data and store it in a suitable data store such as Amazon S3 or Amazon DynamoDB. It also allows them to retrieve the data and feed it into their existing analytics platform.
Musti35
👍 1
Selected: B
Özgür Öztürk on UDEMY has Ayti.tech said that in blog correct answer B
channn
👍 1
Selected: D
vote for D
jdr75
👍 1
Selected: D
Perfectly explained by CaoMengde09 : Let's read again this key sentence : "The company wants to use these data points in its existing analytics platform" So we have already an existing Analytics Platforms which means here that we should only support the architecture not propose a new analytics paltform from scratch. So AWS API Gateway and Lambda are more than enough to bring the data to the client's EXISTING ANALYTICS PLATFORM. Also AWS Kinesis Data Analytics cannot work without already a provisioned AWS Kinesis Data Stream Cluster. So D. Is far from enough to support the architecture
Dr_Chomp
👍 1
D - the KDA service pushes the aggregated data to their analytics tool in real time. the lambda function does nothing and stores nothing in this scenario and makes less sense than option D
TheAbsoluteTruth
👍 2
B. Amazon API Gateway is a fully managed service that makes it easy to create, publish, maintain, monitor, and secure REST APIs. AWS Lambda is a serverless compute service that allows you to execute code in response to events and automatically scale to handle the load. Together, these services enable the creation of a multi-tier architecture that can receive, process and respond to REST API requests in a scalable and secure manner. Using this option, the enterprise can store location data in a persistent database or storage, such as Amazon S3, Amazon DynamoDB or Amazon RDS, and then configure a Lambda function that runs in response to REST API requests to retrieve the location data. In this way, the data points will be accessible from the REST API and can be integrated into the company's existing analytics platform.
nauman001
👍 2
AWS Lambda Now Supports Up to 10 GB Ephemeral Storage
nauman001
👍 1
AWS Lambda, a service for running arbitrary code functions, can be used together to simplify the creation of robust multi-tier applications.
MssP
👍 5
Selected: B
It could be B or D but I prefer B because you take into account "The company wants to use these data points in its existing analytics platform". No need Kinesis for analytics and more expensive than Lambda.
MssP
👍 2
Besides this, look at the question: Which action meets these requirements for storing and retrieving location data? Ask for storing and retrieving, not analisys.
Hemanthgowda1932
👍 1
D is correct Answer
rhm
👍 1
Selected: D
D is correct
mell1222
👍 1
Use AWS IoT to collect and publish location data from the bicycles to an MQTT topic. The bicycles could be equipped with GPS sensors that send data to AWS IoT, which would then publish the data to an MQTT topic. Set up an Amazon Kinesis Data Firehose delivery stream to ingest the data from the MQTT topic and store it in an Amazon S3 bucket. This would allow for easy storage and retrieval of the location data. Use Amazon API Gateway to create a REST API that would allow the analytics platform to access the location data stored in the S3 bucket. Set up AWS Lambda functions to process and transform the location data as required. This could involve filtering or aggregating the data to reduce the amount of data that needs to be stored, or transforming the data into a format that is easier for the analytics platform to consume. Use Amazon CloudWatch to monitor and troubleshoot the various components of the multi-tier architecture. This would allow for easy identification and resolution of any issues that may arise. KDA for storage and retrival
bdp123
👍 1
Selected: D
https://aws.amazon.com/solutions/implementations/aws-streaming-data-solution-for-amazon-kinesis/
Alhaz
👍 1
Selected: B
" existing analytics platform" and hence no need of any other analytics kinesis
vipyodha
👍 2
kda can store data with retention period
bdp123
👍 1
Selected: D
This AWS CloudFormation template deploys a reference architecture that includes the following: An Amazon API Gateway REST API acts as a proxy to Amazon Kinesis Data Streams, adding either an individual data record or a list of data records. An Amazon Cognito user pool is used to control who can invoke REST API methods. Kinesis Data Streams to store the incoming streaming data. An AWS Lambda function processes the records from the data stream. https://aws.amazon.com/solutions/implementations/streaming-data-solution-for-amazon-kinesis/
CaoMengde09
👍 2
Let's read again this key sentence : "The company wants to use these data points in its existing analytics platform" So we have already an existing Analytics Platforms which means here that we should only support the architecture not propose a new analytics paltform from scratch. So AWS API Gateway and Lambda are more than enough to bring the data to the client's EXISTING ANALYTICS PLATFORM. Also AWS Kinesis Data Analytics cannot work without already a provisioned AWS Kinesis Data Stream Cluster. So D. Is far from enough to support the architecture
Maxx
👍 1
Selected: D
I believe option D is more closer ,Kenisis Data Analytics can provide bicycle location as more data points to company’s existing analytics platform through API Gateway , but not getting the question last statement for Storing and retrieving Local Data. More closer Option Is D from all.Kindly comments in reply for this post .
Maxx
👍 1
I believe option D is more closer ,Kenisis Data Analytics can provide bicycle location as more data points to company’s existing analytics platform through API Gateway , but not getting the question last statement for Storing and retrieving Local Data ?! But better option from all is Option D
kerl
👍 1
I select B, Question asking about solutioning a "multi-tier" application to call their existing Analytic Platform via Rest API. So i will use API-Gateway as the front for user to call, and lambda to call the exiting analytic platform n return back to the user.
LionelSid
👍 3
Selected: D
Amazon API Gateway can be used to create a REST API to access the data. Kinesis Data Analytics can be used to process and analyze the location data in real-time and stream it to an existing analytics platform. This solution would provide a way to handle high-volume location data streams and perform real-time analytics on them. Amazon Athena with Amazon S3 could be used for ad-hoc querying and analyzing data stored in S3. But it would not be a real-time solution. Amazon QuickSight with Amazon Redshift could also be used for analyzing data stored in Redshift but again it wouldn't be a real-time solution. Amazon API Gateway with AWS Lambda could be used to create a REST API but it would not provide a way to process and analyze the location data in real-time and stream it to an existing analytics platform.
bullrem
👍 1
Selected: D
D. Use Amazon API Gateway with Amazon Kinesis Data Analytics meets these requirements as it allows the company to store and retrieve location data in real-time and process it using Kinesis Data Analytics. The data can then be accessed from the REST API using Amazon API Gateway. This option allows the company to have real-time access to the location data and use it for analytics.
kerl
👍 2
https://aws.amazon.com/blogs/publicsector/creating-a-serverless-gps-monitoring-and-alerting-solution/ Can the above solution provide clear answer of choosing Lambda(B) or Kinesis Data Analytics? I go for B based on the blog form aws.
remand
👍 3
Selected: B
Only storage and retrieval is needed. Analytics platform is already available.
vesen22
👍 1
So It's B or D?
Zerotn3
👍 2
Selected: B
Use Amazon API Gateway with AWS Lambda.
Mindvision
👍 2
B is the correct answer. "Kinesis Data Analytics" is just to query and analyze data stream, not storing https://aws.amazon.com/kinesis/data-analytics/
Berny
👍 1
Selected: D
you can use Amazon API Gateway to create a REST API that handles incoming requests having location data from the bicycles and sends it to the Kinesis Data Analytics application on the back end. You cannot use Lambda to store and retrieve the location data for analysis Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena cannot be used to build a REST API to consume data from the source. QuickSight is a cloud-native, serverless business intelligence service. Quicksight cannot be used to build a REST API to consume data from the source. Redshift is a fully managed AWS cloud data warehouse.
techhb
👍 1
Selected: D
i choose D,Why because Amazon Kinesis Data Analytics,prepares data for already existing data analytics platform,people choosing lambda are getting confused thinking Kinesis Data Analytics is performing data analytics,Kinesis Data Stream is used for analytics and not https://aws.amazon.com/kinesis/data-analytics/
berks
👍 1
I choose D
Silvestr
👍 3
Selected: B
Keyword: Data points in its existing analytics platform + Data points must be accessible from the REST API + Track the location of its bicycles during peak operating hours They already have an analytics platform, A (Athena) and D (Kinesis Data Analytics) are out of the race even though S3 & APT Gateway Support REST API. Now B and C are in Race. C will not support REST API. So answer should be B as per below details. Now if we talk about data type, we are talking about GEO location data for their bicycles. API Gateway will be support REST API. So, exact solution should be API Gateway with AWS Lambda along with Amazon Kinesis Data Analytics (Assume its used already). CORRECT: “Use Amazon API Gateway with AWS Lambda” is the correct answer
arseyam
👍 3
Selected: D
https://aws.amazon.com/solutions/implementations/streaming-data-solution-for-amazon-kinesis/
duriselvan
👍 1
Ans a is correct S3 is REST API.
Buruguduystunstugudunstuy
👍 7
Selected: D
To store and retrieve location data in a multi-tier architecture that is accessible through a REST API, the most viable option would be to use Amazon API Gateway with Amazon Kinesis Data Analytics which is Option D. Amazon API Gateway is a fully managed service that makes it easy to create, publish, maintain, monitor, and secure APIs. It allows you to create REST APIs that can receive HTTP requests and return responses. Amazon Kinesis Data Analytics is a fully managed service that makes it easy to process and analyze streaming data in real-time. It allows you to run real-time analytics on data streams and batch data using SQL or Java. By using these two services together, you can create a REST API that allows you to store and retrieve location data points in real-time, and run analytics on the data as it is being collected.
Buruguduystunstugudunstuy
👍 3
Why other options are wrong Option A (Amazon Athena with Amazon S3) is not a viable option because Amazon Athena is a querying service that allows you to analyze data stored in Amazon S3 using SQL, but it does not provide a way to store or retrieve data through a REST API. Option B (Amazon API Gateway with AWS Lambda) is not a viable option because AWS Lambda is a serverless compute service that allows you to run code in response to events, but it does not provide a way to store or retrieve data. Option C (Amazon QuickSight with Amazon Redshift) is not a viable option because Amazon QuickSight is a business intelligence service that allows you to create visualizations and dashboards from data stored in various data stores, including Amazon Redshift, but it does not provide a way to store or retrieve data through a REST API.
Richaqua
👍 3
Selected: A
A: Athena has REST API to access and S3 is for storage. Fulfills both the requirements B: API Gateway and Lambda are for retrieval I believe and no storage mechanism C: Quicksight has in-memory storage called SPICE but need to purchase additional capacity for long term storage. D: Kinesis Data Analytics implicitly stores data but is not meant for "storage"
career360guru
👍 3
Selected: B
Option B
anhike
👍 1
Selected: D
"its existing analytics platform" -> Kinesis RESTfull API -> API gateway
aki29
👍 1
Selected: D
for storing and retrieving location data --> using SQL cmd of KDA
lapaki
👍 4
Selected: A
See PDR’s explanation
aaok
👍 1
It seems to be a problem from SAA-C02, but it's difficult to get an answer that satisfies everyone so far. If you are not aiming for a perfect score, you will intuitively want to choose B or D, which has the most votes.
javitech83
👍 1
Selected: D
i think is D. Kinesis is oriented for analytic and almost real time. I do not see how lambda would solve the storage need
kmliuy73
👍 1
Amazon Kinesis Data Analytics is Real-time analytics on Kinesis Data Streams & Firehose using SQL, not store data ...
PDR
👍 12
Selected: A
looking through the answers and comments and Im not convinced that B or D , the most voted options are correct and in fact it looks to me like A might be the answer here. B - not correct as does not fulfil the data storage requirement as others have mentioned D - better as provides REST API access and temp storage in kinesis analytics, but the question is asking for storage so we have to assume that it needs longer term storage A - Athena supports REST API access https://docs.aws.amazon.com/athena/latest/APIReference/Welcome.html and of course S3 fulfils the storage requirement Put simply , you would store the data in S3 and configure Athena to point to the S3 location and the customers Analytics program would query the data via Athena REST API - meets all requirements. Surprised no one else has suggested this .... unless I am missing something completely so am prepared to be proved wrong!
Futurebones
👍 1
I agree with you. You put my thought well.
JayBee65
👍 1
A does seem to make sense at meeting the requirements of the question
5up3rm4n
👍 3
Answer is B. Kinesis Data Streams does not persist data. It also only ingests data from Kinesis Data Stream and Firehose, and outputs to Kinesis Data Stream, Firehose and Lambda.
mabotega
👍 1
Selected: D
This question is about location of company´s bicycles during peak operating hours", so, the data is coming from their application and must be checked in real-time during peak operating hours, so, it requires Kinesis Data Analytcs and API Gateway supports the Kinesyis. https://docs.aws.amazon.com/apigateway/latest/developerguide/integrating-api-with-aws-services-kinesis.html
rjam
👍 3
Selected: D
B is wrong as the question specifies about storing and retrieving location data. APIGateway and lambda cannot store data. Amazon API Gateway with Kinesis Data Analytics: Amazon API Gateway is a fully managed service that allows you to publish, maintain, monitor, and secure APIs at any scale. Amazon API Gateway offers two options to create RESTful APIs, HTTP APIs and REST APIs, as well as an option to create WebSocket APIs. You can use Kinesis Data Analytics to transform and analyze streaming data in real-time with Apache Flink. Kinesis Data Analytics enables you to quickly build end-to-end stream processing applications for log analytics, clickstream analytics, Internet of Things (IoT), ad tech, gaming, etc. The four most common use cases are streaming extract-transform-load (ETL), continuous metric generation, responsive real-time analytics, and interactive querying of data streams. Kinesis Data Analytics for Apache Flink applications provides your application 50 GB of running application storage per Kinesis Processing Unit (KPU).
JayBee65
👍 1
Yes D can store and retrieve, but it's doing so much more, aimed at providing analytics, which is not being asked for here, whereas A offers just what is asked for.
BD12
👍 1
B If REST API means, there API gateway should be there.
Gil80
👍 5
Selected: B
Why B? 1. QuickSight doesn't support REST API. 2. They already have an analytics platform, A (Athena) and D (Kinesis Data Analytics) are out of the race even though S3 & APT Gateway Support REST API. B & C are an option. C will not support REST API. So answer should be B
Nigma
👍 1
D is the correct. The question is asking for storing and retrieving
PS_R
👍 1
Selected: D
KDA also stores data for 365 days, so i feel D
PoisonBlack
👍 2
I saw this question on the exam and choose D. Lol.
Onimole
👍 3
D might be the right choice When Should I Use Amazon Kinesis Data Analytics? Amazon Kinesis Data Analytics enables you to quickly author SQL code that continuously reads, processes, and stores data in near real time. Using standard SQL queries on the streaming data, you can construct applications that transform and provide insights into your data. Following are some of example scenarios for using Kinesis Data Analytics:
Onimole
👍 12
Weird Q as they already have their own data analysis platform Hopefully i dont see this question in the exam lol
Onimole
👍 1
it can store according to the doc There is no way to lambda to store data which is part of the requirements
rob74
👍 2
B Lambda and API
Hunkie
👍 3
Selected: B
They already have an existing analytics platform
Dsouzaf
👍 1
to track the location of its bicycles during peak operating hours. This lines tells it is streaming data and hence Amazon Kinesis Data Analytics
Six_Fingered_Jose
👍 83
Selected: D
I dont understand why you will vote B? how are you going to store data with just lambda? > Which action meets these requirements for storing and retrieving location data In this use case there will obviously be a ton of data and you want to get real-time location data of the bicycles, and to analyze all these info kinesis is the one that makes most sense here.
JackLo
👍 1
B is more appropriate the question contains to retrieve, Kinesis doesn't have such function, Lambda can set custom function as you like
MutiverseAgent
👍 5
B might work but D works better. B requieres API gateway + lambda for data input & output, whereas D is a broader solution, as Kinesis Data Analytics APIs can be used to extract and process data better that API Gateway + Lambdas. API Supports integration with several languages. Also, Kinesis is highly recommended for telemetry data which is the question scenario. @See Kinesys flexible API (https://aws.amazon.com/documentation-overview/kinesis-data-analytics/)
aadityaravi8
👍 1
100% agree
JiyuKim
👍 2
But KDA also cannot store data.
a070112
👍 10
Lambda isn't storing the data themselves. It's triggering the data store to the company's "existing data analytics platform"
kmliuy73
👍 5
Real-time analytics on Kinesis Data Streams & Firehose using SQL, not store db ...
rob74
👍 7
I vote D because company HAS its analitcs Platform, Why pay?. Kinesis is for analys not for storing. Can you explain? Thanks
UWSFish
👍 4
I don't think you need to worry about storing data. The question states their is an existing platform.
Six_Fingered_Jose
👍 5
https://aws.amazon.com/blogs/aws/real-time-hotspot-detection-in-amazon-kinesis-analytics/
dave9994
👍 1
The question is about storing and retrieving, API GW satisfies retrieving part, and Kinesys handles storing part. I would go with D.
ArielSchivo
👍 113
Selected: B
API Gateway is needed to get the data so option A and C are out. “The company wants to use these data points in its existing analytics platform” so there is no need to add Kynesis. Option D is also out. This leaves us with option B as the correct one.
Tsige
👍 10
While API Gateway and Lambda can work together for processing requests, this setup doesn't efficiently handle continuous real-time data streaming and analysis, which is required for tracking the bicycle locations. Lambda is stateless and is better suited for on-demand execution, not for real-time analytics of streaming data. So, the correct option is D
MutiverseAgent
👍 12
B might work but D works better. B requieres API gateway + lambda for data input & output, whereas D is a broader solution, as Kinesis Data Analytics APIs can be used to extract and process data better that API Gateway + Lambdas. Also, Kinesis is highly recommended for telemetry data which is the question scenario. @See Kinesys flexible API (https://aws.amazon.com/documentation-overview/kinesis-data-analytics/)
alfonso_ciampa
👍 12
You are right, but it clearly say "store data". AWS Lambda don't store data, Kinesis could.
ces26015
👍 7
i dont understand the use of a lambda function here, maybe if there would be need to transform the data, can you explain?
bullrem
👍 13
AWS Lambda is a serverless compute service that can be used to run code in response to specific events, such as changes to data in an Amazon S3 bucket or updates to a DynamoDB table. It could be used to process the location data, but it doesn't provide storage solution. Therefore, it would not be the best option for storing and retrieving location data in this scenario.
Lilibell
👍 1
The answer is B
Stiffler1
👍 1
why d?
Comments & Corrections
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Expert Analysis
Why the Answer Is Correct
Option B (Amazon API Gateway with AWS Lambda) is the correct answer because it directly satisfies all stated requirements in a single, cohesive multi-tier pattern. API Gateway provides the REST API endpoint that the question explicitly requires for data access. AWS Lambda sits behind API Gateway, processes incoming location data points, and persists them to a data store (e.g., Amazon DynamoDB) or forwards them into the company's existing analytics platform. This forms a classic serverless multi-tier architecture: API Gateway (presentation tier) → Lambda (application tier) → DynamoDB/existing analytics (data tier). The scalability of both API Gateway and Lambda handles peak-hour traffic bursts without provisioning infrastructure.
Why the Other Options Are Wrong
Option D (API Gateway with Kinesis Data Analytics) fails because Kinesis Data Analytics requires a Kinesis Data Streams or Kinesis Data Firehose as its input source — it cannot be directly connected to API Gateway. The option does not include a Kinesis Data Streams component, so the ingestion path from API Gateway is architecturally incomplete. As rvca231 correctly pointed out, "Kinesis Data Analytics requires a Kinesis Data Streams or Kinesis Data Firehose as input streams, so you cannot directly connect it to API Gateway."
Option A (Athena with S3) provides storage and query capabilities but has no REST API component; the question explicitly states "The data points must be accessible from the REST API," which Athena+S3 alone cannot satisfy. Option C (QuickSight with Redshift) is a BI/dashboard and data warehousing combination designed for analytical querying, not for real-time REST API access to location data, and similarly lacks an API Gateway component.
Community Comment Notes
The community is split between B and D. ArielSchivo correctly argues that since "the company wants to use these data points in its existing analytics platform," there is no need to introduce Kinesis, leaving B as the answer. Six_Fingered_Jose pushes back on B, questioning "how are you going to store data with just lambda?" — but Lambda can write to DynamoDB or any downstream store, so this objection doesn't hold. Tsige argues Lambda "isn't storing the data themselves" and that the setup "doesn't efficiently handle continuous real-time data streaming," favoring D — however, the question doesn't require Kinesis Streams ingestion, and KDA can't be directly wired to API Gateway. rvca231 makes the decisive technical argument that Kinesis Data Analytics cannot be connected directly to API Gateway, which rules out D entirely.
Official Reference
Exam Strategy
When a question explicitly states that data must be accessible from a REST API, immediately look for Amazon API Gateway among the options — its presence or absence often eliminates half the choices. Then verify that the second service in the pairing can both process and persist data in a way that completes the multi-tier pattern.
Frequently Asked Questions
Why can't Amazon API Gateway connect directly to Amazon Kinesis Data Analytics?
Kinesis Data Analytics requires a Kinesis Data Streams or Kinesis Data Firehose as its input source. API Gateway cannot serve as a direct input to Kinesis Data Analytics, so the ingestion path in option D is architecturally incomplete.
How does AWS Lambda store data if it is a compute service?
Lambda does not store data itself, but it can write incoming location data to Amazon DynamoDB, Amazon S3, or directly into the company's existing analytics platform as part of its execution logic behind API Gateway.
Related Analysis
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