Amazon Keyspaces now helps you read and write data in Apache Spark more easily

Amazon Keyspaces (for Apache Cassandra), a scalable, highly available, and fully managed Cassandra-compatible database service, now helps you read and write data in Apache Spark more easily by using the open-source Spark Cassandra Connector.

Apache Spark is an open-source engine for large-scale data analytics. Customers use Apache Spark to perform analytics on data stored in Amazon Keyspaces more efficiently. Customers also use Amazon Keyspaces to provide applications consistent, single-digit-millisecond read access to analytics data from Spark. Now, you can read and write data between Amazon Keyspaces and Spark more easily by using the open-source Spark Cassandra Connector. Amazon Keyspaces support for the Spark Cassandra Connector helps you run Cassandra workloads in Spark-based analytics pipelines more easily by using a fully managed and serverless database service. With Amazon Keyspaces, you don’t need to worry about Spark competing for the same underlying infrastructure resources as your tables. Amazon Keyspaces tables scale up and down automatically based on your application traffic.

There’s no additional cost to enable Amazon Keyspaces support for the Spark Cassandra Connector. Support for Spark Cassandra Connector is available in all AWS Regions where AWS offers Amazon Keyspaces.

To learn more, see Reading and writing data between Amazon Keyspaces and Apache Spark.