{"category":"5849d7233bcfb30f00dde741","parentDoc":null,"project":"54d8224d25e90a0d00db54ff","user":"54d822008180e40d005789a3","version":"5849d7223bcfb30f00dde740","updates":["5547b06cccd25d00000d6cd7","5547b093e0b260000007c0fb","57e0d0128929550e00f1d96d"],"_id":"5849d7233bcfb30f00dde763","next":{"pages":[],"description":""},"createdAt":"2015-02-16T07:34:30.379Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":0,"body":"Apache Ignite<sup>tm</sup> In-Memory Data Fabric is a high-performance, integrated and distributed in-memory platform for computing and transacting on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based or flash-based technologies.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/tQKXxoWzT9aGBR4NrPFf_apache-ignite.png\",\n        \"apache-ignite.png\",\n        \"735\",\n        \"223\",\n        \"#a1694a\",\n        \"\"\n      ],\n      \"caption\": \"\"\n    }\n  ]\n}\n[/block]\n##Features\nYou can view Ignite as a collection of independent, well-integrated, in-memory components geared to improve performance and scalability of your application. Some of these components include:\n\n  * [Advanced Clustering](doc:cluster)\n  * [Data Grid](doc:data-grid) \n  * [SQL Grid](doc:sql-grid) \n  * [Streaming & CEP](doc:streaming--cep) \n  * [Compute Grid](doc:compute-grid) \n  * [Service Grid](doc:service-grid)\n  * [Ignite File System](https://apacheignite-fs.readme.io/docs/in-memory-file-system)\n  * [Distributed Data Structures](doc:queue-and-set) \n  * [Distributed Messaging](doc:messaging) \n  * [Distributed Events](doc:events) \n  * [Hadoop Accelerator](https://apacheignite-fs.readme.io/docs/hadoop-accelerator)\n  * [Spark Shared RDDs](https://apacheignite-fs.readme.io/docs/ignite-for-spark)\n\nIn addition to Spark and Hadoop, Ignite integrates with a variety of other technologies and products. The integrations are intended to simplify coupling of Apache Ignite and other technologies, used in your applications or services, in order to either perform a transition to Apache Ignite smoothly or to boost an existed solution by plugging Ignite into it.\n\nThe rest of existed integrations are covered under dedicated [documentation domain](https://apacheignite-mix.readme.io/docs/getting-started).","excerpt":"In-Memory Data Fabric","slug":"what-is-ignite","type":"basic","title":"What is Ignite","__v":0,"childrenPages":[]}

What is Ignite

In-Memory Data Fabric

Apache Ignite<sup>tm</sup> In-Memory Data Fabric is a high-performance, integrated and distributed in-memory platform for computing and transacting on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based or flash-based technologies. [block:image] { "images": [ { "image": [ "https://files.readme.io/tQKXxoWzT9aGBR4NrPFf_apache-ignite.png", "apache-ignite.png", "735", "223", "#a1694a", "" ], "caption": "" } ] } [/block] ##Features You can view Ignite as a collection of independent, well-integrated, in-memory components geared to improve performance and scalability of your application. Some of these components include: * [Advanced Clustering](doc:cluster) * [Data Grid](doc:data-grid) * [SQL Grid](doc:sql-grid) * [Streaming & CEP](doc:streaming--cep) * [Compute Grid](doc:compute-grid) * [Service Grid](doc:service-grid) * [Ignite File System](https://apacheignite-fs.readme.io/docs/in-memory-file-system) * [Distributed Data Structures](doc:queue-and-set) * [Distributed Messaging](doc:messaging) * [Distributed Events](doc:events) * [Hadoop Accelerator](https://apacheignite-fs.readme.io/docs/hadoop-accelerator) * [Spark Shared RDDs](https://apacheignite-fs.readme.io/docs/ignite-for-spark) In addition to Spark and Hadoop, Ignite integrates with a variety of other technologies and products. The integrations are intended to simplify coupling of Apache Ignite and other technologies, used in your applications or services, in order to either perform a transition to Apache Ignite smoothly or to boost an existed solution by plugging Ignite into it. The rest of existed integrations are covered under dedicated [documentation domain](https://apacheignite-mix.readme.io/docs/getting-started).