• Apache Ignite is a distributed database for high-performance computing with in-memory speed.
• Ignite scales up and out across memory and disk.
  • By default, Ignite operates in a pure in-memory mode.
  • But, by toggling a single configuration setting, you can turn a cluster into a database that can grow beyond the cluster's memory capacity.
• Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs available for Java, C#, C++, Python, and other programming languages.
  • Seamlessly join group, aggregate, and order your distributed in-memory and on-disk data.
• Ignite can operate strongly and consistently, providing full support for distributed ACID transactions.
  • Transact across multiple cluster nodes, caches, tables, and partitions.
• With traditional databases, you use stored procedures written in a language such as PL/SQL for in-place calculations.
  • With Ignite, you use modern JVM languages, C# or C++, to develop and execute custom tasks across your distributed database:
• Ignite machine learning uses built-in algorithms and tools, as well as TensorFlow integration, to enable the building of scalable machine learning models and avoid costly data transfers.
  • Train, deploy, evaluate, and update your ML and DL models continuously and at scale.
• With relational databases, you use triggers to react to certain events.
  • With Ignite, you deploy continuous queries written in a modern programming language such as Java or C# and process streams of changes on the database and application side.

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