For Mission Critical In-Memory Data Grid Use Cases

The GridGain® in-memory computing platform, built on Apache® Ignite, enables new or existing applications built on disk-based databases to run 1,000x faster and scale out to petabytes of in-memory data. The GridGain Enterprise Edition adds features to Apache Ignite with make GridGain easier to deploy, manage and secure in production environments:

Enterprise Edition

The GridGain Enterprise Edition is deployed as an in-memory computing layer between the application and data layers. The GridGain platform includes powerful features for in-memory computing including an in-memory data grid, in-memory database, streaming analytics and a continuous learning framework for real-time machine and deep learning. GridGain includes the only available in-memory data grid with support for ACID transaction and ANSI-99 SQL, including DDL and DML.

GridGain works with all popular RDBMS, NoSQL and Hadoop databases, requiring no rip-and-replace of the existing database infrastructure. With ACID compliant transactions and ANSI SQL-99 support, the GridGain Enterprise Edition is a powerful in-memory addition for OLTP, OLAP or HTAP use cases. GridGain can be deployed on-premises, on public or private clouds, or on hybrid environments.

GridGain Enterprise Edition Features

The GridGain Enterprise Edition includes the following features in addition to the core features of Apache Ignite.

Enterprise-Grade Security

The GridGain Enterprise Edition Enterprise-Grade Security provides extensible and customizable authentication and security capabilities. It includes both a Grid Authentication SPI and a Grid Secure Session SPI to satisfy a variety of security requirements.

Network Segmentation Protection

Network Segmentation Protection detects any network disruption within the grid to prevent transactional data grids from developing a ‘split brain’ scenario. The options for handling these network occurrences are fully configurable to handle these situations the way you need to for a variety of use cases.

Rolling Production Updates

The Rolling Production Updates feature enables you to co-deploy multiple versions of our software on nodes across the cluster and allows them to co-exist as you roll out new versions. This prevents any downtime when performing software upgrades.

Data Center Replication

GridGain reliably replicates data on a per-cache basis across two or more regions connected by wide area networks. This allows geographically remote data centers to maintain consistent views of data. With GridGain reliability and predictability, Data Center Replication ensures business continuity and can be used as part of a disaster recovery plan. Data Center Replication integrates with your application so that caches marked for replication are automatically synchronized across the WAN link.

Management & Monitoring Tool

Our GUI-based Management and Monitoring Tool provides a unified operations, management and monitoring system for GridGain deployments. It provides a deep management and monitoring view into all aspects of GridGain operations – from HPC and Data Grid to Streaming, and Hadoop acceleration, via standard dashboards, advanced charting of performance metrics, and grid health (telemetry) views, among many other features.

Oracle® GoldenGate Integration

The Oracle GoldenGate integration in the GridGain Enterprise Edition provides real-time data integration and replication into a GridGain cluster from different environments. When users configure GoldenGate integration replication, the GridGain in-memory computing platform will automatically receive updates from the connected source database, converting the data from a database relational model to cache objects.

GridGain Connector for Apache Kafka

The GridGain Connector for Apache® Kafka® makes it easy to leverage Apache Kafka and Confluent® to create high performance streaming analytics and applications based on streaming data. The GridGain Connector for Apache Kafka is certified by Confluent. It is a native integration which allows applications using the connector to ingest massive data sets from Kafka and Confluent or publish to them, and also process and analyze the data in-memory with unlimited horizontal scalability on the GridGain in-memory computing platform.

GridGain Data Lake Accelerator

The GridGain Data Lake Accelerator solves the challenges of digital businesses that need to improve real-time analytics and decision automation by enriching real-time data with historical data stored in data lakes. The Data Lake Accelerator provides bi-directional integration with Hadoop to accelerate data lake access. This integration brings the historical data into the same in-memory computing layer as the operational data, enabling computing and real-time analytics on the combined data.