RDI support for federated caches, sharded data sources and multiple pipelines

Modern applications rarely rely on one database. Data is often distributed across regions, business units, shards, and different technology stacks. Bringing that data together in real time should not require users to build and operate a separate integration architecture for every source.

Redis Data Integration (RDI) is evolving to make that experience simpler.

Unifying data with multi-source pipelines

RDI Software and RDI in Redis Cloud now support multi-source pipelines, allowing users to connect multiple source databases to a single pipeline and load captured and transformed data into one Redis target database.

This makes it easier to consolidate data from systems such as Snowflake, MongoDB, Oracle, MySQL, PostgreSQL, RDS, and Aurora into a unified, low-latency data layer in Redis.

Why use multi-source pipelines?

Multi-source pipelines are useful when an application needs data that is distributed across multiple systems but must be available together in real time. For example:

• Combine user, account, transaction, and data from different systems to support real-time fraud prevention and other risk checks.
• Unify data from regional, tenant-specific, or acquired business systems into a single read-optimized view.
• Build a consolidated, in-sync portfolio view when products and their components are stored across different databases or schemas.
• Support federated-cache architectures and sharded data sources by hydrating one Redis data layer from multiple databases.

By consolidating data before it reaches the application, multi-source pipelines reduce the need to stitch data together in application code, minimize independent integration deployments, and simplify the path to real-time application experiences.

Next up: multi-pipeline support

Multi-source pipelines consolidate your sources. Multi-pipeline support consolidates your deployments, so a single RDI install can serve an entire integration architecture rather than one pipeline within it.

With multi-pipeline, users will be able to operate multiple RDI pipelines as part of a broader integration architecture. This will make it easier to model more complex environments, separate workloads and ingestion flows, and scale RDI deployments as data integration requirements grow.

Multi-pipeline support is coming to RDI soon. More details on availability, configuration, and supported deployment options will follow as the capability progresses toward release.

Multi-pipeline support will strengthen RDI’s role as the integration layer between distributed operational data and Redis applications. Users will be able to evolve from a single integration flow to a more flexible architecture without losing the benefits of real-time capture, transformation, and delivery into Redis.

Building toward a more flexible RDI

Multi-source pipelines are an important step toward simplifying distributed data integration. Multi-pipeline support is the next evolution, giving users more flexibility as their environments, workloads, and real-time application needs expand.

RDI is making it easier to turn distributed source data into a unified, actionable Redis data layer.