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APACHE IGNITE
Distributed database and in-memory computing platform
Apache-2.0
ABOUT
ML feature stores, real-time inference pipelines, and large-scale data processing need a data platform that combines the speed of in-memory access with the reliability of durable storage and the expressiveness of SQL. Using separate caches, databases, and compute engines creates data movement overhead and operational complexity. Apache Ignite solves this by providing a distributed in-memory data platform with ACID transactions, ANSI SQL support, machine learning primitives, and compute grid capabilities — all in one system. Data stays in memory across the cluster for fast access, while durable storage and distributed computing eliminate the need to shuttle data between tiers.
INTEGRATION GUIDE
1. Power a real-time ML feature store that serves features for online inference from in-memory data with ACID guarantees
2. Run distributed ML training and scoring jobs directly on in-memory data without moving it to a separate compute cluster
3. Cache model predictions, embeddings, and intermediate results with sub-millisecond access across an inference serving fleet
4. Deploy a high-throughput SQL-queryable cache layer for real-time analytics dashboards monitoring model performance
5. Build a distributed compute grid for large-scale data preprocessing and feature engineering that runs in-place on cached data
TAGS
in-memory-computingdistributed-databasecachingsqldata-platformapachejava