Migrate from Amazon Kinesis Data Analytics for SQL to Amazon Managed Service for Apache Flink and Amazon Managed Service for Apache Flink Studio

Amazon Kinesis Data Analytics for SQL is a data stream processing engine that helps you run your own SQL code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics. AWS has made the decision to discontinue Kinesis Data Analytics for SQL, effective January 27, 2026. In this post, we explain why we plan to end support for Kinesis Data Analytics for SQL, alternative AWS offerings, and how to migrate your SQL queries and workloads.

Overview of Kinesis Data Analytics for SQL

The following diagram illustrates the workflow for using Kinesis Data Analytics for SQL.

Kinesis Data Analytics for SQL has been denoted a legacy offering since 2021 on our marketing pages, the AWS Management Console, and public documentation. In this time, we haven’t added new functionality or expanded Kinesis Data Analytics for SQL to new AWS Regions. However, we continue to actively maintain and patch the offering and support customers using the service. We will continue to undertake these activities.

To help you plan and migrate away from Kinesis Data Analytics for SQL, we will discontinue the offering gradually:

• On October 15, 2025, you won’t be able to create new Kinesis Data Analytics for SQL applications from this time, but will be able to run any existing applications as normal.
• We will delete any remaining customer applications on January 27, 2026. You won’t be able to start or operate your Kinesis Data Analytics for SQL applications and support will no longer be available for Kinesis Data Analytics for SQL from this time.

Overview of Managed Service for Apache Flink and Apache Flink Studio

Kinesis Data Analytics for SQL, which was launched in 2016, predates several popular AWS data stream processing offerings, such as Amazon Managed Service for Apache Flink and Amazon Managed Service for Apache Flink Studio. We have found that customers often want to use these newer offerings over Kinesis Data Analytics for SQL.

Amazon Managed Service for Apache Flink is a serverless, low-latency, highly scalable, and highly available real-time stream processing service. Apache Flink is a distributed open source engine for processing data streams. These managed Flink-based offerings provide functionality not available in Kinesis Data Analytics for SQL and can help you build end-to-end streaming pipelines and maintain the accuracy and timeliness of data. For example, Amazon Managed Service for Apache Flink supports built-in scaling, exactly-once processing semantics, multi-language support (including SQL), over 40 source and destination connectors, durable application state, and more

We see customers migrating their Kinesis Data Analytics for SQL workloads to take advantage of the advanced features available with managed Flink offerings. Customers running SQL queries typically select Amazon Managed Service for Apache Flink Studio. Amazon Managed Service for Apache Flink Studio allows you to create a notebook, which is a web-based development environment. With notebooks, you get a simple interactive development experience combined with the advanced capabilities provided by Flink. Amazon Managed Service for Apache Flink Studio uses Apache Zeppelin as the notebook, and uses Flink as the stream processing engine. Amazon Managed Service for Apache Flink Studio notebooks seamlessly combine these technologies to make advanced analytics on data streams accessible to developers of all skill sets. Notebooks are provisioned quickly and provide a way for you to instantly view and analyze your streaming data. Zeppelin provides your Amazon Managed Service for Apache Flink Studio notebooks with a complete suite of analytics tools, including the following capabilities:

• Visualizing data
• Exporting data to files
• Controlling the output format for straightforward analysis
• Turning the notebook into a scalable, production application

The following diagram illustrates a common workflow for Managed Service for Apache Flink.

Unlike Kinesis Data Analytics for SQL, Managed Service for Apache Flink adds the following SQL support:

• Joining stream data between multiple streams in Amazon Kinesis Data Streams, or between a Kinesis data stream and an Amazon Managed Streaming for Apache Kafka (Amazon MSK) topic
• Real-time visualization of transformed data in a data stream
• Using Python scripts or Scala programs within the same application
• Changing offsets of the streaming layer

Another benefit of Amazon Managed Service for Apache Flink is the improved scalability of the solution post-deployment, because you can scale the underlying resources to meet demand. In Kinesis Data Analytics for SQL, scaling is performed by adding more pumps to persuade the application into adding more resources.

Migrate to Managed Service for Apache Flink

For more information about migrating Kinesis Data Analytics for SQL to Amazon Managed Service for Apache Flink Studio, see Migrate from Amazon Kinesis Data Analytics for SQL Applications to Amazon Managed Service for Apache Flink Studio. Additionally, we have provided guidance in our public documentation, including sample code for how to recreate 17 common Kinesis Data Analytics for SQL queries in Amazon Managed Service for Apache Flink Studio, which we will continue to expand over time. We have created step by step migration guidance for customers using Amazon Data Firehose as a source, or who want to use user-defined functions in Amazon Managed Service for Apache Flink . We also provide documentation to help customers migrating machine learning workloads from Kinesis Data Analytics for SQL to Amazon Managed Service for Apache Flink.

Conclusion

In this post, we outlined how we plan to discontinue Kinesis Data Analytics for SQL and why we’re taking these steps. We recommend migrating your Kinesis Data Analytics for SQL workloads to Amazon Managed Service for Apache Flink or Apache Flink Studio, and we have provided resources to help you get started with your migration. If you need more help, you can ask questions in  re:Post, making sure to tag Kinesis Data Analytics for SQL.

About the author

Julian Payne is a Principal Product Manager at AWS. He is passionate about building products and features to help customers innovate using real-time data processing applications in the cloud. Outside of work he writes and illustrates graphic novels.