RedisGears Documentation
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Infinitely programmable data processing in Redis
RedisGears is a dynamic framework that enables developers to write and execute functions that implement data flows in Redis, while abstracting away the data’s distribution and deployment. These capabilities enable efficient data processing using multiple models in Redis with infinite programmability, while remaining simple to use in any environment.
Introduction to RedisGears from RedisConf 2020 keynote
With a built-in C-API and Python interpreter, RedisGears lets you use fully fledged Python scripts and libraries to process data inside Redis.
Write your functions against a standalone Redis database and deploy them to production clusters—with no changes required.
RedisGears lets you process events and streams faster by running in memory next to your data in Redis.
RedisGears enables multi-model data processing without the complexity of multiple clients and database connectors.
Use Redis as your frontend database to improve application performance, while guaranteeing that all changes are written to your backend databases.
With RedisGears, accessing and processing data using multiple data structures and data models happens at the speed of memory.
Write functions that react to events in Redis, such as new messages in a stream, or write operations in a key.
Combine data in different Redis data structures and modules, transform them, and write them into others using RedisGears.
Use functions to create tensors from data in Redis, combine them with application requests, and serve them to AI models for fast inferencing.
RedisGears has three main components:
RedisGears minimizes the execution time and the data flow between shards by running your functions as close as possible to your data.
On top of these three core components, RedisGears also includes a fast, low-level C-API that integrates via Python for programmability.
RedisInsight is an intuitive visual tool to explore and analyze your data in Redis.
Use RedisInsight with RedisGears to:
As benefits, you get faster turnarounds when building your RedisGears scripts.
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