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Redis Data Integration

Transform your slow application data into real-time data

Synchronize existing databases with Redis Enterprise to mirror application data. That means slow applications can operate at real-time speeds without refactoring, writing new code, or exhausting integration efforts.

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Digital transformation directly on Redis Enterprise

Redis Data Integration (RDI) creates a data streaming pipeline that mirrors data from an existing database to Redis Enterprise. The result: applications can access data at in-memory speeds.

RDI integrates legacy databases with Redis Enterprise in a two-way flow. It performs data ingestion and transformation as well as downstream data changes from Redis Enterprise back into your other databases.

RDI Ingest

RDI’s ingest flow capability includes a Change Data Capture (CDC) platform to capture changes in the source database. It allows developers to ingest and export data in near real-time and to stream data from the legacy database into a Redis database. Within the RDI process, the data is filtered, transformed, and mapped to Redis data types such as Hash or JSON. RDI then writes the data to the destination Redis database–and your other applications (the modern, up-to-date ones) can interact with the Redis database without complicated workarounds.

The data synchronizes with the legacy database, so its internal systems keep working. And when your big modernization project does happen, you have all the current data without another migration step.

Effectively, RDI helps you transform legacy data into real-time data so you can focus on your current application suite and not on your data transformation.

Redis Data Integration Transformation Engine

Use cases

Improve application performance

Improve application performance

Accelerate and scale applications by offloading queries to Redis. You can extend the life of legacy databases that can’t be easily replaced.

Create a microservices data layer

Create a microservices data layer

Avoid data bottlenecks from slow databases. Provide a high-performance data layer that scales with your microservices architecture.

Modernize applications

Modernize applications

Capture, filter, and transform data while moving it into Redis. Support advanced data models without replacing existing databases.

The Redis Data Integration feature set

  • High availability of Debezium Server and RDI
  • Hard rejected entries handling in Dead Letter Queue (DLQ)
  • Data extraction modes: Initial snapshot and CDC for stream changes
  • Declarative transformations: Filter condition, Redis key pattern, change field names, add field, remove field, nest
  • Supported Redis data types: Hash, JSON, Set, Stream
  • Developer tools: RDI CLI scaffold and trace commands
  • Operator tools: RDI CLI, Grafana dashboard (metrics via Prometheus exporter)

We will keep adding features to RDI to simplify the integration of Redis Enterprise in a downstream flow. Look for upcoming support for additional caching patterns such as write-behind, write-through, and read-through.

Work with the tools you know

RDI lets you connect your old and slow database and transform it into a real-time data layer. Source databases supported today: Oracle, PostgreSQL, MySQL, MariaDB, Percona XtraDB, Microsoft SQL Server, Cassandra (including DataStax DSE).

Redis is creating an ecosystem of trusted partners so you can choose the data replication system that fits your needs.

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Join the public preview

Want to explore the features for yourself? Existing Redis Enterprise customers can download the RDI CLI package and follow the steps in the quick start guide.

If you are not a Redis Enterprise customer, the first step is to install Redis Enterprise Software for Kubernetes. Then download the RDI CLI package and follow the steps in its quick start guide.