GridGain® is a powerful Redis® alternative for demanding computing use cases. Redis is primarily an in-memory key-value store used for caching data, although the product is often promoted as a database. GridGain, which is built on Apache® Ignite™, is a full featured in-memory computing platform which includes an in-memory data grid, in-memory database, and streaming analytics. Companies that use or are considering Redis for demanding use cases may find, however, that Redis is unable to meet their needs in use cases where a true in-memory data grid or in-memory database is required to deliver advanced, real-time performance.
The data grid capabilities of both GridGain and Redis partition and cache data in memory. Both products can be scaled out across distributed clusters. However, there are many differences in the way Redis and GridGain support caching, transactions, persistence, and data querying. The GridGain in-memory computing platform is a powerful alternative to Redis because it includes many additional features not found in Redis that are highly valuable when moving to in-memory computing.
For simple Redis data caching use cases, the GridGain Cloud allows users to rapidly deploy a distributed in-memory cache as a service and access it using ANSI-99 SQL, key-value or REST APIs. The result is an in-memory computing platform-as-a-service, which offers the simplicity of SQL, for caching use cases. GridGain Cloud can be massively scaled out and can be deployed in minutes.
GridGain In-Memory Computing Platform vs Redis
When using an in-memory data grid to add speed and scale to existing applications:
- Redis is primarily an in-memory “cache-aside” key-value cache used by developers to improve the read performance of their applications. It requires coding within the application to add the cache, and coding and configuration to keep the data in the cache up to date relative to any underlying data sources. It does not fully support SQL, so relational data must typically be mapped to another model.
- GridGain can be used as more than a cache. GridGain can be used as an in-memory data grid which slides between existing application and data layers without having to rip-and-replace or rewrite the application or databases. By replacing existing JDBC or ODBC drivers with the GridGain drivers, GridGain can sit in the path of SQL or other queries and support ACID transactions as an inline read- and write-through cache. It keeps data in sync with the underlying database by updating the cache following a successful commit by the underlying database.
When using the systems as a distributed SQL and key-value database:
- Redis can be used as a key-value store for application data. Developers appreciate how simple it is to manage data within an application using the Redis APIs.
- GridGain can be used as a distributed key-value database. But GridGain can also be used as an in-memory distributed SQL database. Its optional native persistence capability allows RAM to hold a subset of the full dataset which resides on disk. It provides immediate availability on restart without having to wait for data to be loaded into memory first. GridGain also offers ACID transaction support with pessimistic locking, unlike Redis.
Used as an in-memory data grid or in-memory database, GridGain also provides the ability to partition data based on data affinity and use massively parallel processing (mpp) to improve performance and scalability. GridGain provides built-in stream processing, analytics and machine learning capabilities that have enabled companies to deliver new types of applications for digital transformation and omnichannel customer experience initiatives that were either too costly or too complex to deliver in the past. Collocated processing has helped reduce network traffic in deployments by as much as 100x, which is one reason companies have moved from Redis to GridGain.
More Information About GridGain vs Redis
Learn more about GridGain as a Redis alternative by downloading our in-depth GridGain and Redis feature comparison. It details how GridGain Redis compare in 22 different categories including:
- Distributed Caching, Data Structures, Queries, Compute, Messaging and Events
- ACID Compliant Transactions and Locks
- Persistence and Data Loading
- Security and Audit
- In-Memory Streaming
- Configuration and Grid Management
- Supported Platforms, Standards and Integrations
- Cloud and Virtualization Support