Distributed Databases Using In-Memory Computing
Organizations facing the challenges of massively scaling their relational database often consider distributed database solutions. These solutions shard and distribute the database across a cluster of servers. Such distributed database solutions can greatly increase the performance of applications built on infrastructure-limited databases.
The GridGain® in-memory computing platform can be installed between the application and data layers and uploads data from the underlying disk-based RDBMS, NoSQL or Hadoop datastores into RAM. The results is scalability to petabytes of data and a 1,000x or greater improvement in processing speed without manually sharding the underlying database.
This is accomplished using the distributed in-memory data grid capability of GridGain which is deployed across a cluster of commodity servers. The system accelerates compute by moving data from disk into RAM and also by leveraging the GridGain Compute Grid to use all of the compute power of the cluster for massive parallel processing. The system is highly scalable because new nodes can be added to the GridGain cluster at any time and the automatic rebalancing feature will balance the in-memory data between nodes while redundantly maintaining the data across nodes in the cluster.
GridGain Transactional Persistence
When using the GridGain Transactional Persistence feature, all of your data and all of your SQL indexes are kept on disk, allowing GridGain to be fully operational from disk. You can then define whether all or only a portion of the distributed database dataset is kept in-memory. The combination of Persistent Store and the GridGain platform's advanced SQL capabilities allows GridGain to serve as a distributed transactional SQL database, spanning both memory and disk.
GridGain supports ACID transactions so data changes at the application layer are written to the underlying RDBMS. GridGain's ANSI-99 SQL support allows you to interact with your distributed database on the GridGain cluster using standard SQL including DML and DDL commands. The result is a platform which can power OLTP, OLAP and hybrid transactional/analytical processing (HTAP) use cases.
Additional Capabilities of the GridGain Distributed Database
GridGain removes the scalability limitations of many common relational databases and allows you to create:
- A Distributed MySQL Database
- A Distributed PostgreSQL Database
- A Distributed Oracle Database
- A Distributed Version of Any Popular RDBMS
GridGain is ANSI SQL-99 compliant with full data indexing so it can support distributed NoSQL and HDFS while also providing a number of database-specific advantages such as: