Apache Ignite

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  1. 7c3cac2 IGNITE-12950 Added check of partition sizes to GridDhtPartitionsStateValidator, even if update counters are different. Fixes #8645 by Ivan Mironovich · 7 hours ago master
  2. 28c738a IGNITE-13567 Fixed incorrect value of the joiningNodeClient flag (#8350) by Pavel Pereslegin · 35 hours ago
  3. b8914bc IGNITE-13958 .NET: Add implicit Java type registration in ExecuteJavaTask (#8635) by Nikolay · 2 days ago
  4. 65a02ca IGNITE-13912 Fixed calculation of the number of segments to be deleted - Fixes #8650. by Kirill Tkalenko · 2 days ago
  5. 66f7d6a IGNITE-14015 Tracing SQL: tracing of SELECT queries causes incorrect span inheritance (#8675) by Mikhail Petrov · 2 days ago

Apache Ignite

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What is Apache Ignite?

Apache Ignite is a distributed database for high-performance computing with in-memory speed.

Multi-Tier Storage

Apache Ignite is designed to work with memory, disk, and Intel Optane as active storage tiers. The memory tier allows using DRAM and Intel® Optane™ operating in the Memory Mode for data storage and processing needs. The disk tier is optional with the support of two options -- you can persist data in an external database or keep it in the Ignite native persistence. SSD, Flash, HDD, or Intel Optane operating in the AppDirect Mode can be used as a storage device.

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Ignite Native Persistence

Even though Apache Ignite is broadly used as a caching layer on top of external databases, it comes with its native persistence - a distributed, ACID, and SQL-compliant disk-based store. The native persistence integrates into the Ignite multi-tier storage as a disk tier that can be turned on to let Ignite store more data on disk than it can cache in memory and to enable fast cluster restarts.

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ACID Compliance

Data stored in Ignite is ACID-compliant both in memory and on disk, making Ignite a strongly consistent system. Ignite transactions work across the network and can span multiple servers.

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ANSI SQL Support

Apache Ignite comes with a ANSI-99 compliant, horizontally scalable, and fault-tolerant SQL engine that allows you to interact with Ignite as with a regular SQL database using JDBC, ODBC drivers, or native SQL APIs available for Java, C#, C++, Python, and other programming languages. Ignite supports all DML commands, including SELECT, UPDATE, INSERT, and DELETE queries as well as a subset of DDL commands relevant for distributed systems.

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Machine Learning and High-Performance Computing

Apache Ignite Machine Learning is a set of simple, scalable, and efficient tools that allow building predictive machine learning models without costly data transfers. The rationale for adding machine and deep learning to Apache Ignite is quite simple. Today's data scientists have to deal with two major factors that keep ML from mainstream adoption.

High-performance computing (HPC) is the ability to process data and perform complex calculations at high speeds. Using Apache Ignite as a high-performance compute cluster, you can turn a group of commodity machines or a cloud environment into a distributed supercomputer of interconnected Ignite nodes. Ignite enables speed and scale by processing records in memory and reducing network utilization with APIs for data and compute-intensive calculations. Those APIs implement the MapReduce paradigm and allow you to run arbitrary tasks across the cluster of nodes.