use-cases/in-memory-database.html - ignite-website - Git at Google

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 <!DOCTYPE html>
 <html lang="en">
 <head>

     <link rel="canonical" href="https://ignite.apache.org/use-cases/in-memory-database.html"/>
     <meta charset="utf-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">

     <meta name="description"
           content="Apache Ignite, as an in-memory database, is a high-performant system-of-records that is capable of
           storing and querying large data sets from memory as well as disk without requiring to warm up the memory tier
           on cluster restarts."/>

     <title>In-Memory Database - Apache Ignite</title>

     <!--#include virtual="/includes/styles.html" -->


 </head>
 <body>

 <!--#include virtual="/includes/header.html" -->
 <article>
     <header>
         <div class="container">
             <h1><strong>In-Memory Database</strong> With Apache Ignite</h1>
         </div>
     </header>
     <div class="container">

         <p>
             Apache Ignite® is a distributed in-memory database that scales horizontally across memory and disk tiers.
             Ignite supports ACID transactions, ANSI-99 SQL, key-value, compute, machine learning, and other data
             processing APIs. As a database, Ignite uses memory, disk or Intel® Optane™ as active storage tiers and
             removes the need to cache all the data and the need for memory warm-ups.
         </p>
         <img class="diagram-right img-responsive" src="/images/svg-diagrams/database.svg" alt="In-Memory Database diagram" />


         <h2>Multi-Tier Storage</h2>
         <p>
             Apache Ignite works with memory, disk, and Intel Optane as active storage tiers. This architecture combines,
             in one system, the advantages of in-memory computing with disk durability and strong consistency.
         </p>
         <p>
             When the native persistence is enabled, Ignite allows you to control the amount of memory it should
             consume. Depending on the memory space available, Ignite either caches the full data set in memory or
             keeps only the most frequently used data there and retrieves missing records from disk when needed.
             For instance, if there are 100 records and the memory of your system can accommodate only 20 of them,
             then all 100 records will be stored on disk and only 20 records will be cached in memory for better
             performance.
         </p>

         <p>
             The following are the primary advantages of Ignite memory management architecture:
         </p>
         <ul class="page-list">
             <li>
                 Multi-tiered storage - Ignite treats disk as an active storage layer allowing to
                 cache a subset of the data in memory and query both in-memory and disk-only records with SQL and
                 all other available APIs.
             </li>
             <li>
                 Instantaneous cluster restarts - Ignite becomes fully operational from disk upon a cluster
                 startup or restarts without requiring to preload or warm up the memory tier.
             </li>
         </ul>

         <h2>Better High-Availability With Instantaneous Cluster Restarts</h2>

         <p>
             Ignite native persistence takes away the trouble of time-consuming memory warm-ups on cluster restarts.
             When the native persistence is enabled, Ignite stores a superset of data on disk treats it as one of the
             storage layers. Hence, Ignite starts reading data from the persistence layer as soon as the cluster becomes
             active. As you begin to run the queries, the memory tier is warmed up in the background with the data Ignite
             accesses from the disk.
         </p>

         <h2>Avoiding Network Impact on Performance With Co-located Processing</h2>

         <p>
             Disk-centric systems, like RDBMS or NoSQL, generally use the classic client-server approach when
             transferring data from the server to the client-side where it gets processed and then discarded. This
             approach does not scale very well because moving data over the network is the most expensive operation
             in a distributed system.
         </p>
         <p>
             Many distributed databases, including Apache Ignite, support a more scalable approach called co-located
             processing, which eliminates or significantly reduces network traffic by running application logic right
             on the cluster nodes. This approach executes data or compute-intensive queries, including distributed
             SQL with JOINs, exactly where the data resides.
         </p>

         <div class="jumbotron jumbotron-fluid">
             <div class="container">
                 <div class="title display-6">Learn More</div>
                 <hr class="my-4">
                 <div class="row">
                     <div class="col-sm-6">
                         <ul>
                             <li><a href="/arch/multi-tier-storage.html">Multi-Tier Storage <i
                                     class="fa fa-angle-double-right"></i></a></li>
                             <li><a href="/arch/native-persistence.html">Native Persistence <i
                                     class="fa fa-angle-double-right"></i></a></li>
                             <li><a href="/features/collocated-processing.html">Co-located Processing <i
                                     class="fa fa-angle-double-right"></i></a></li>
                             <li><a href="/features/sql.html">Distributed SQL <i class="fas fa-angle-double-right"></i></a>
                             </li>
                             <li><a href="/features/acid-transactions.html">ACID Transactions <i
                                     class="fa fa-angle-double-right"></i></a></li>
                         </ul>
                     </div>
                     <div class="col-sm-6">
                         <ul>
                             <li><a href="/features/machinelearning.html">Machine and Deep Learning <i
                                     class="fa fa-angle-double-right"></i></a></li>
                             <li><a href="/use-cases/in-memory-data-grid.html">Ignite as an In-Memory Data Grid <i
                                     class="fa fa-angle-double-right"></i></a></li>
                             <li><a href="/use-cases/in-memory-cache.html">Ignite as an In-Memory Cache <i
                                     class="fa fa-angle-double-right"></i></a></li>
                             <li><a href="/use-cases/digital-integration-hub.html">Ignite as a Digital Integration Hub <i
                                     class="fa fa-angle-double-right"></i></a></li>
                         </ul>
                     </div>
                 </div>
             </div>
         </div>
     </div>
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	Licensed to the Apache Software Foundation (ASF) under one
	or more contributor license agreements. See the NOTICE file
	distributed with this work for additional information
	regarding copyright ownership. The ASF licenses this file
	to you under the Apache License, Version 2.0 (the
	"License"); you may not use this file except in compliance
	with the License. You may obtain a copy of the License at

	http://www.apache.org/licenses/LICENSE-2.0

	Unless required by applicable law or agreed to in writing,
	software distributed under the License is distributed on an
	"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
	"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
	KIND, either express or implied. See the License for the
	specific language governing permissions and limitations
	under the License.
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	<!DOCTYPE html>
	<html lang="en">
	<head>

	<link rel="canonical" href="https://ignite.apache.org/use-cases/in-memory-database.html"/>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">

	<meta name="description"
	content="Apache Ignite, as an in-memory database, is a high-performant system-of-records that is capable of
	storing and querying large data sets from memory as well as disk without requiring to warm up the memory tier
	on cluster restarts."/>

	<title>In-Memory Database - Apache Ignite</title>

	<!--#include virtual="/includes/styles.html" -->


	</head>
	<body>

	<!--#include virtual="/includes/header.html" -->
	<article>
	<header>
	<div class="container">
	<h1><strong>In-Memory Database</strong> With Apache Ignite</h1>
	</div>
	</header>
	<div class="container">

	<p>
	Apache Ignite® is a distributed in-memory database that scales horizontally across memory and disk tiers.
	Ignite supports ACID transactions, ANSI-99 SQL, key-value, compute, machine learning, and other data
	processing APIs. As a database, Ignite uses memory, disk or Intel® Optane™ as active storage tiers and
	removes the need to cache all the data and the need for memory warm-ups.
	</p>
	<img class="diagram-right img-responsive" src="/images/svg-diagrams/database.svg" alt="In-Memory Database diagram" />


	<h2>Multi-Tier Storage</h2>
	<p>
	Apache Ignite works with memory, disk, and Intel Optane as active storage tiers. This architecture combines,
	in one system, the advantages of in-memory computing with disk durability and strong consistency.
	</p>
	<p>
	When the native persistence is enabled, Ignite allows you to control the amount of memory it should
	consume. Depending on the memory space available, Ignite either caches the full data set in memory or
	keeps only the most frequently used data there and retrieves missing records from disk when needed.
	For instance, if there are 100 records and the memory of your system can accommodate only 20 of them,
	then all 100 records will be stored on disk and only 20 records will be cached in memory for better
	performance.
	</p>

	<p>
	The following are the primary advantages of Ignite memory management architecture:
	</p>
	<ul class="page-list">
	<li>
	Multi-tiered storage - Ignite treats disk as an active storage layer allowing to
	cache a subset of the data in memory and query both in-memory and disk-only records with SQL and
	all other available APIs.
	</li>
	<li>
	Instantaneous cluster restarts - Ignite becomes fully operational from disk upon a cluster
	startup or restarts without requiring to preload or warm up the memory tier.
	</li>
	</ul>

	<h2>Better High-Availability With Instantaneous Cluster Restarts</h2>

	<p>
	Ignite native persistence takes away the trouble of time-consuming memory warm-ups on cluster restarts.
	When the native persistence is enabled, Ignite stores a superset of data on disk treats it as one of the
	storage layers. Hence, Ignite starts reading data from the persistence layer as soon as the cluster becomes
	active. As you begin to run the queries, the memory tier is warmed up in the background with the data Ignite
	accesses from the disk.
	</p>

	<h2>Avoiding Network Impact on Performance With Co-located Processing</h2>

	<p>
	Disk-centric systems, like RDBMS or NoSQL, generally use the classic client-server approach when
	transferring data from the server to the client-side where it gets processed and then discarded. This
	approach does not scale very well because moving data over the network is the most expensive operation
	in a distributed system.
	</p>
	<p>
	Many distributed databases, including Apache Ignite, support a more scalable approach called co-located
	processing, which eliminates or significantly reduces network traffic by running application logic right
	on the cluster nodes. This approach executes data or compute-intensive queries, including distributed
	SQL with JOINs, exactly where the data resides.
	</p>

	<div class="jumbotron jumbotron-fluid">
	<div class="container">
	<div class="title display-6">Learn More</div>
	<hr class="my-4">
	<div class="row">
	<div class="col-sm-6">
	<ul>
	<li><a href="/arch/multi-tier-storage.html">Multi-Tier Storage <i
	class="fa fa-angle-double-right"></i></a></li>
	<li><a href="/arch/native-persistence.html">Native Persistence <i
	class="fa fa-angle-double-right"></i></a></li>
	<li><a href="/features/collocated-processing.html">Co-located Processing <i
	class="fa fa-angle-double-right"></i></a></li>
	<li><a href="/features/sql.html">Distributed SQL <i class="fas fa-angle-double-right"></i></a>
	</li>
	<li><a href="/features/acid-transactions.html">ACID Transactions <i
	class="fa fa-angle-double-right"></i></a></li>
	</ul>
	</div>
	<div class="col-sm-6">
	<ul>
	<li><a href="/features/machinelearning.html">Machine and Deep Learning <i
	class="fa fa-angle-double-right"></i></a></li>
	<li><a href="/use-cases/in-memory-data-grid.html">Ignite as an In-Memory Data Grid <i
	class="fa fa-angle-double-right"></i></a></li>
	<li><a href="/use-cases/in-memory-cache.html">Ignite as an In-Memory Cache <i
	class="fa fa-angle-double-right"></i></a></li>
	<li><a href="/use-cases/digital-integration-hub.html">Ignite as a Digital Integration Hub <i
	class="fa fa-angle-double-right"></i></a></li>
	</ul>
	</div>
	</div>
	</div>
	</div>
	</div>
	</article>
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