What Is GridGain?
GridGain is a middleware-class product developed by the company of the same name.
As a middleware, GridGain is an in-memory computing platform that is designed to tackle speed and scale challenges. But what does that mean? In practice, it signifies that GridGain is capable of storing and processing your data right in RAM across a cluster of interconnected machines. GridGain APIs are developed in a way to minimize network traffic between cluster nodes and your applications. Not only complex SQL queries with JOINs can perform at scale, but your custom Java/.NET/C++ logic can be executed in-place on the cluster machines resulting in an unprecedented performance boost.
As a company, GridGain developed the software that became Apache Ignite, donating the original code to the Apache Software Foundation (ASF) in 2014. Apache Ignite, one of the fastest ASF projects to graduate to top-level status, is now a top 5 ASF project in terms of contributions and dev-list activity and is downloaded millions of times annually. GridGain continues being among the major ASF contributors who are striving to increase adoption of Apache Ignite across open source community and companies with "the open-source first" policy. Besides the commitment to open source, GridGain works and powers mission-critical deployments of large enterprises that benefit from extra features available in GridGain platform only as well as from production support, professional and managed services.
What Can You Do with GridGain?
We’ve seen many usage scenarios of GridGain with various deployment modes and architectures. However, the most typical two are GridGain as an in-memory data grid (IMDG) and GridGain as a system of records. As an IMDG, GridGain solves speed and scale problems of existing solutions that are usually powered by relational or NoSQL databases. A GridGain in-memory cluster is deployed between the existing application and database. Once the data from the underlying database loads into the IMDG, the IMDG processes all the reads and writes, ensuring transactional consistency for RDBMS-backed architectures. As a system of records, GridGain is used by green-field and modern applications that are looking for both speed and scale with guarantees of durability and data consistency for disk-based databases.
It’s important to note that even though GridGain belongs to the class of in-memory products, it can store anywhere from 0 to 100% of the data in memory and keep the total data set in a broad range of non-volatile memory: from disk or SSD to the latest persistent memory such as Intel Optane. This allows companies to combine in-memory speed with the lower cost and durability of non-volatile storage.
So how do companies, large and small, use GridGain? Our customers use GridGain to add speed and scale to a broad range of real-time applications, including:
Existing custom real-time or batch-based applications
New core banking systems including credit cards authorization and payment systems
Web-scale and mobile applications and APIs
Equity and other securities trading and analytics
High performance computing (HPC)
Fraud detection and regulatory compliance
eCommerce and healthcare benefits management
Voice over IP (VoIP) routing and management
The Internet of Things (IoT)
Machine learning (ML) and deep learning (DL)
GridGain is available in three editions: Community, Enterprise, and Ultimate.
GridGain Community Edition is for those who need features of Apache Ignite with a regular release schedule for improvements and bug fixes. This Edition is completely free, includes all the capabilities of Apache Ignite and hardened for production deployments.
If you want everything in the Community Edition, but also require some enterprise features as enterprise-grade security, data center replication or connectors for various enterprise storage or streaming technologies then go for GridGain Enterprise Edition.
If, on top of all that, you deploy GridGain as a system of records keeping all the data in Ignite persistence then GridGain Ultimate Edition should be your choice for cluster-wide snapshots/backups and recovery management tools.
Moreover, keep in mind that production support and professional services are available not only for GridGain Editions but for Apache Ignite deployments as well.
Migrating From Apache Ignite
For the most part, you can migrate from Apache Ignite to GridGain without major issues.
To migrate, stop your server and replace Apache Ignite binaries with GridGain binaries. Data will be preserved when you restart servers, but you may need to account for differences in some features. Here are some possible issues:
GridGain snapshots were developed separately from Apache Ignite. The implementations are not compatible. If you used Apache Ignite snapshots in your project, you will need to implement GridGain snapshots instead.
Ignite CDC (Change Data Capture) is an experimental feature in Apache Ignite, and as such it does not have exact counterpart in GridGain. Instead, GridGain Enterprise and Ultimate editions offer Data Center Replication to replicate cache data.
If you used Apache Ignite CDC, you will need to implement Data Center Replication or use an alternative solution.
Calcite SQL Support
Calcite SQL engine is not supported in GridGain and there are currently no plans to implement it in GridGain 8.x versions. GridGain 9 release is planned to include full support for Calcite SQL.
Cellular affinity is an experimental mode in Apache Ignite. As such, it is not implemented in GridGain.
Service interceptors ("middleware") are an experimental feature in Apache Ignite. It is currently not available in GridGain.
Custom Execution Context
It is currently not possible to set up a custom execution context in GridGain.
Service Call Context
In GridGain, you cannot retrieve arrays of custom objects.
Read-Repair is an experimental API in Apache Ignite. Due to losses in performance it was not transferred to GridGain.
Apache, Apache Ignite, the Apache feather and the Apache Ignite logo are either registered trademarks or trademarks of The Apache Software Foundation.