For new projects, we recommend that you use the new Managed Service for Apache Flink Studio over Kinesis Data Analytics for SQL Applications. Managed Service for Apache Flink Studio combines ease of use with advanced analytical capabilities, enabling you to build sophisticated stream processing applications in minutes.
Document History for Amazon Kinesis Data Analytics
The following table describes the important changes to the documentation since the last release of Amazon Kinesis Data Analytics.
API version: 2015-08-14
Latest documentation update: May 8, 2019
| Change | Description | Date |
|---|---|---|
| Tagging Kinesis Data Analytics Applications | Use application tagging to determine per-application costs, control access, or for user-defined purposes. For more information, see Using Tagging. | May 8, 2019 |
| Logging Kinesis Data Analytics API Calls with Amazon CloudTrail | Amazon Kinesis Data Analytics is integrated with Amazon CloudTrail, a service that provides a record of actions taken by a user, role, or an Amazon service in Kinesis Data Analytics. For more information, see Using Amazon CloudTrail. | March 22, 2019 |
| Kinesis Data Analytics available in Frankfurt region | Kinesis Analytics is now available in the Europe (Frankfurt) Region region. For more information, see and Endpoints: Kinesis Data Analytics. | July 18, 2018 |
| Use reference data in the console | You can now work with application reference data in the console. For more information, see Example: Adding Reference Data to a Kinesis Data Analytics Application . | July 13, 2018 |
| Windowed query examples | Example applications for windows and aggregation. For more information, see Examples: Windows and Aggregation . | July 9, 2018 |
| Testing applications | Guidance on testing changes to application schema and code. For more information, see Testing Applications . | July 3, 2018 |
| Example applications for preprocessing data | Additional code samples for REGEX_LOG_PARSE, REGEX_REPLACE, and DateTime operators. For more information, see Examples: Transforming Data . | May 18, 2018 |
| Increase in size of returned rows and SQL code | The limit for the size for a returned row is increased to 512 KB, and the limit for the size of the SQL code in an application is increased to 100 KB. For more information, see Limits. | May 2, 2018 |
| Amazon Lambda function examples in Java and .NET | Code samples for creating Lambda functions for preprocessing records and for application destinations. For more information, see Creating Lambda Functions for Preprocessing and Creating Lambda Functions for Application Destinations. | March 22, 2018 |
New HOTSPOTS function |
Locate and return information about relatively dense regions in your data. For more information, see Example: Detecting Hotspots on a Stream (HOTSPOTS Function). | March 19, 2018 |
| Lambda function as a destination | Send analytics results to a Lambda function as a destination. For more information, see Using a Lambda Function as Output. | December 20, 2017 |
New RANDOM_CUT_FOREST_WITH_EXPLANATION function |
Get an explanation of what fields contribute to an anomaly score in a data stream. For more information, see Example: Detecting Data Anomalies and Getting an Explanation (RANDOM_CUT_FOREST_WITH_EXPLANATION Function). | November 2, 2017 |
| Schema discovery on static data | Run schema discovery on static data stored in an Amazon S3 bucket. For more information, see Using the Schema Discovery Feature on Static Data. | October 6, 2017 |
| Lambda preprocessing feature | Preprocess records in an input stream with Amazon Lambda before analysis. For more information, see Preprocessing Data Using a Lambda Function. | October 6, 2017 |
| Auto scaling applications | Automatically increase the data throughput of your application with auto scaling. For more information, see Automatically Scaling Applications to Increase Throughput. | September 13, 2017 |
| Multiple in-application input streams | Increase application throughput with multiple in-application streams. For more information, see Parallelizing Input Streams for Increased Throughput. | June 29, 2017 |
| Guide to using the Amazon Web Services Management Console for Kinesis Data Analytics | Edit an inferred schema and SQL code using the schema editor and SQL editor in the Kinesis Data Analytics console. For more information, see Step 4 (Optional) Edit the Schema and SQL Code Using the Console. | April 7, 2017 |
| Public release | Public release of the Amazon Kinesis Data Analytics Developer Guide. | August 11, 2016 |
| Preview release | Preview release of the Amazon Kinesis Data Analytics Developer Guide. | January 29, 2016 |