GridGain and Redis Feature Comparison
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Redis Enterprise (and their respective open source projects where relevant) compare in 25 categories.
Redis® is an open-source (BSD licensed), in-memory data structure used as a database, cache and message broker, as stated on Redis.io. Redis, when combined with Redis Enterprise (the commercially supported version from Redis Labs), is widely known as one of the most popular caches and key-value stores on the market due to its cost and simplicity for developers. Redis (which we will now use to refer to Redis and Redis Enterprise) is used primarily by developers in applications for session caching, full page cache, message queue applications, leaderboards and counting.
GridGain®, built on the Apache Ignite® open source project, is an in-memory computing platform that’s used as a distributed in-memory data grid, in-memory SQL and key-value database, stream processing and analytics engine, and a continuous learning framework for machine and deep learning. At first glance, GridGain and Redis seem similar. Both include functionality for caching data in memory. Both can partition data and be scaled out across distributed clusters. But that’s where the similarities end.
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Redis Enterprise (and their respective open source projects where relevant) compare in 25 different categories including:
- Use Cases
- 3rd Party Database Support and Persistence
- Support for Native Persistence
- Distributed SQL and Queries
- Memory Architecture and Optimization
- Distributed Architecture
- Data Rebalancing
- Distributed Computing
- In-Memory Streaming and Integration with Apache Spark
- Security and Audit
- Configuration and Grid Management
- Supported Platforms, Standards and Out-of-the-Box Integration
- Cloud and Virtualization Support