Redis Data Integration: Your fast lane from legacy systems to the AI era on AWS

Enterprises aren’t short on valuable data. They’re short on ways to effectively use it. For years, your most important operational data has lived in Oracle, PostgreSQL, MySQL, and even modern cloud databases like AWS RDS and Aurora. That data is the backbone of your business, but the systems holding it weren’t built for the AI era’s demands: sub-millisecond speed, unified real-time access, and intelligence at scale.

You know you need that data in the cloud. You know you need it to be powering AI use cases. But the usual modernization path looks painful: high-risk migrations, fragile custom pipelines, and months of engineering time spent moving data instead of creating value.

Redis Data Integration (RDI) changes that.

The direct path to speed and intelligence

RDI with Redis Cloud and AWS, gives you a way to modernize by continuously syncing with your primary database. Keep your system of record exactly where it’s today. Pull data into Redis on AWS in near-real time, making your data available for modern caching and search workloads. Redis Cloud on AWS can serve as both your real-time data layer and your AI knowledge base, so you don’t have to stitch together separate systems.

This is the stable-meets-fast architecture modern enterprises need. Your source of truth stays authoritative. Your apps get a high-performance, cloud-native data layer designed for AI.

And because RDI captures and applies changes in seconds, your Redis cache stays fresh. Your experience stays responsive. And your teams stop waiting for full migrations before delivering new capabilities.

How RDI works

RDI uses Change Data Capture to follow every insert, update, and delete in your supported databases. It translates those changes into native Redis structures and syncs them into Redis Cloud on AWS through an enterprise-grade. Secure CDC pipeline.

The workflow is simple but powerful:

Initial sync. RDI bulk-loads the entire dataset into Redis with no custom ETL and no operational hassle. Continuous streaming. As new transactions occur, Redis is updated within seconds. From that moment on, your application can read from Redis, not the legacy database, getting sub-millisecond latency and immediate scalability. And because Redis Cloud is fully managed on AWS, the infrastructure burden shifts off your team.

A modern foundation without rewriting everything

The Redis + AWS approach gives you a pragmatic, incremental modernization path. No big-bang cutovers. No rewriting your entire application. No reliance on slow, expensive read replicas.

You just sync your data and start unlocking new use cases:

• AI and Vector Search. Combine fresh operational data with vector embeddings for semantic intelligence at scale. RDI syncs the latest data into Redis, and your embedding pipeline (e.g., Bedrock Titan or another embedding model) can generate vectors that Redis stores and indexes for AI-ready retrieval.
• RAG on AWS. Redis integrates natively as a Bedrock Knowledge Base vector store, providing embedded and up-to-date knowledge to LLMs and AgentCore once embeddings have been generated.
• Online Feature Store: Redis is a proven online store for features on AWS (real-time feature retrieval and updates) and integrates with common feature store frameworks.
• Low-latency APIs. Serve high-volume workloads with predictable sub-millisecond response times.
• Recommendation engines. Keep fast-changing product and user data in sync for real-time personalization.
• Operational analytics. Power dashboards and decision systems without overloading your primary database.

This is AI enablement without the migration headaches.

Redis and AWS: Better together

AWS provides the secure, scalable cloud foundation enterprises trust. Redis Cloud adds the high-speed data and AI capabilities modern applications demand. And RDI ensures your legacy systems can participate in this architecture immediately.

Together, you get:

• Fully managed Redis Cloud on AWS
• Native integration with Bedrock Knowledge Base as a vector store, enabling AgentCore-based agents to retrieve data once embeddings have been generated.
• First-class support for semantic caching, routing, and agent memory patterns through Redis AI ecosystem tools and integrations.
• Built-in at-least-once delivery, ordering guarantees, and observability for your pipelines
• High-performance vector search and semantic features
• Effortless elastic scaling for unpredictable workloads

If you’re tired of brittle ETL jobs, stale caches, and costly read replicas, this combination is a breath of fresh air. With RDI, Redis stays in sync. Your applications stay fast. Your teams stay focused on building what matters.

Is RDI the right fit?

RDI is built for organizations that rely on relational systems of record but need dramatically better performance and flexibility. It’s the right tool when:

• Your read-heavy workloads are outgrowing Oracle, PostgreSQL, MySQL, or other supported databases.
• You want an easier path to expose operational data to AWS AI services.
• Your microservices need a fast, scalable data layer.
• Your teams want a managed, configurable pipeline instead of maintaining custom ETL and CDC jobs.

AI is redefining what customers expect. Legacy systems alone can’t meet those expectations. Redis, AWS, and RDI give you a clean, reliable way to modernize without disruption and unlock the value stored in your on-prem databases.

Your data is ready for AI long before you’re ready for a full migration. With RDI, you can start that journey today, securely, incrementally, and with confidence.

If you're ready to accelerate modernization or bring your operational data into the AI era with Redis and AWS, we’re here to help.