Storing and Retrieving Bicycle Location Data via REST API

SAA-C03 By islever Editorial Last updated

Design scalable and loosely coupled architectures. Design highly available and/or fault-tolerant architectures. Determine high-performing database solutions.

Short 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.

Question

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?
  1. Use Amazon Athena with Amazon S3.
  2. Use Amazon API Gateway with AWS Lambda. Correct Answer
  3. Use Amazon QuickSight with Amazon Redshift.
  4. Use Amazon API Gateway with Amazon Kinesis Data Analytics.

Key Takeaways

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.

Common mistake: 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.

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

https://docs.aws.amazon.com/lambda/latest/dg/with-apigateway.html

This link opens the official vendor documentation in a new tab.

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.

More SAA-C03 FAQ →

Discussion 172 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 30 of 172

  1. Six_Fingered_Jose 👍 83 Answered 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.
  2. 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.
  3. PDR 👍 12 Answered 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!
  4. 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/)
  5. Onimole 👍 12
    Weird Q as they already have their own data analysis platform Hopefully i dont see this question in the exam lol
Show 25 more comments
  1. alfonso_ciampa 👍 12
    You are right, but it clearly say "store data". AWS Lambda don't store data, Kinesis could.
  2. 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
  3. a070112 👍 10
    Lambda isn't storing the data themselves. It's triggering the data store to the company's "existing data analytics platform"
  4. Buruguduystunstugudunstuy 👍 7 Answered 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.
  5. rvca231 👍 7 Answered 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
  6. small_zipgeniuis 👍 7 Answered 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
  7. rob74 👍 7
    I vote D because company HAS its analitcs Platform, Why pay?. Kinesis is for analys not for storing. Can you explain? Thanks
  8. 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?
  9. 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/)
  10. MehulKapadia 👍 5 Answered 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
  11. Gil80 👍 5 Answered 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
  12. MssP 👍 5 Answered 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.
  13. 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.
  14. Six_Fingered_Jose 👍 5
    https://aws.amazon.com/blogs/aws/real-time-hotspot-detection-in-amazon-kinesis-analytics/
  15. kmliuy73 👍 5
    Real-time analytics on Kinesis Data Streams & Firehose using SQL, not store db ...
  16. cookieMr 👍 4 Answered 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.
  17. farnamjam 👍 4 Answered 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.
  18. 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
  19. UWSFish 👍 4
    I don't think you need to worry about storing data. The question states their is an existing platform.
  20. HeliosABC 👍 4 Answered D
    Track location, it should be streaming
  21. lapaki 👍 4 Answered A
    See PDR’s explanation
  22. rjam 👍 3 Answered 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).
  23. PaPi_z 👍 3 Answered 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.
  24. bignatov 👍 3 Answered 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.
  25. 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.

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