Increase the performance and scalability of real-time applications and external databases.
An in-memory data grid (IMDG) is an advanced read-through/write-through cache that is deployed on top of multiple databases.
Applications write to and read from the grid, and the grid propagates changes to the underlying data stores in a consistent way.
Co-location is the main IMDG feature. It organizes related data for storage in the same node and enables low latency with high throughput computing.
Co-located applications can access in-memory data without network movement.
In an in-memory data grid queries are processed at high speeds and scaled to multiple nodes, because there's no distance between data and applications.
Enable you to request, join, and group distributed datasets.
Execute logic close to the data, thus eliminating expensive data shuffling over the network.
Allow the seamless implementation of event-driven architectures.
When native persistence is enabled, Ignite stores both data and indexes
on disk, thus eliminating the time-consuming cache warm-up step.
Native persistence keeps a full copy of data on disk, so you are free
to cache a subset of records in memory.
If a required data record is missing from memory, Ignite reads the record from the disk automatically.
Increase the performance and scalability of real-time applications and external databases.
Support high-performance computing.
Cache data that is scattered across databases.
improved its online channel by implementing in-memory solutions. They leveraged an in-memory data grid to achieve faster time-to-market, and data flexibility across digital channels.
used in-memory computing platforms to meet increasing demand for performance and scalability.
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Read the In-Memory Database article
In-Memory Database