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<h1 class="h1 innerhero__h1 innerhero__mega">Distributed Database For <br />High‑Performance Applications <br />With In‑Memory Speed</h1>
<div class="innerhero__h2 h4 pt-2">Scale Across Memory And Disk Without Compromise</div>
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<a class="frontcard" href="https://blogs.apache.org/ignite/entry/apache-ignite-momentum-highlights-from" target="_blank"
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<div class="container forntcodes">
<h2 class="h3">Use Ignite Core Capabilities To Start Easily <br />And Scale Faster</h2>
<div class="forntcodes__wrap flexi jsTabWrap pt-4">
<div class="forntcodes__menu">
<ul class="fz20">
<li><a class="active" href="#" data-ftablink="frontcode-1">Multi-Tier Storage</a></li>
<li><a href="#" data-ftablink="frontcode-2">Distributed SQL</a></li>
<li><a href="#" data-ftablink="frontcode-3">ACID Transactions</a></li>
<li><a href="#" data-ftablink="frontcode-4">Compute APIs</a></li>
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<li><a href="#" data-ftablink="frontcode-6">Continuous Queries</a></li>
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<a class="forntcodes__menumore fz20" href="/features/">View all features</a>
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<div class="forntcodes__tab active" data-ftab="frontcode-1">
<p class="forntcodes__tabtitle fz20 pb-1">Multi-Tier Storage</p>
<p>
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:
</p>
<div class="forntcodes__innertabs jsTabWrap">
<div class="nativecode__tabctrls flexi">
<a class="nativecode__link active" href="#" data-tablink="nativeTabXML">XML</a><a class="nativecode__link" href="#" data-tablink="nativeTabJava">Java</a
><a class="nativecode__link" href="#" data-tablink="nativeTabNET">C#/.NET</a>
</div>
<div class="nativecode__tabs">
<div class="nativecode__tab active" data-tab="nativeTabXML">
<pre class="nativecode__codebox"> <code class="xml"><bean class="org.apache.ignite.configuration.IgniteConfiguration">
<property name="dataStorageConfiguration">
<bean class="org.apache.ignite.configuration.DataStorageConfiguration">
<property name="defaultDataRegionConfiguration">
<bean class="org.apache.ignite.configuration.DataRegionConfiguration">
<property name="persistenceEnabled" value="true"/>
</bean>
</property>
</bean>
</property>
</bean></code></pre>
</div>
<div class="nativecode__tab" data-tab="nativeTabJava">
<pre class="nativecode__codebox"> <code class="java">IgniteConfiguration cfg = new IgniteConfiguration();
DataStorageConfiguration storageCfg = new DataStorageConfiguration();
// Enable Ignite Persistence
storageCfg.getDefaultDataRegionConfiguration().setPersistenceEnabled(true);
// Using the new storage configuration
cfg.setDataStorageConfiguration(storageCfg);
</code></pre>
</div>
<div class="nativecode__tab" data-tab="nativeTabNET">
<pre class="nativecode__codebox"> <code class="csharp">var cfg = new IgniteConfiguration
{
DataStorageConfiguration = new DataStorageConfiguration
{
DefaultDataRegionConfiguration = new DataRegionConfiguration
{
Name = "Default_Region",
PersistenceEnabled = true
}
}
};
</code></pre>
</div>
</div>
<div class="forntcodes__bottom"><a class="button" href="/arch/multi-tier-storage.html">Learn More About Multi-Tier Storage</a></div>
</div>
<!-- /.forntcodes__innertabs-->
</div>
<!-- /.forntcodes__tab1 (END Multi-Tier Storage)-->
<div class="forntcodes__tab" data-ftab="frontcode-2">
<p class="forntcodes__tabtitle fz20 pb-1">Distributed SQL</p>
<p>
Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs that are available for Java, C#, C++, Python, and other programming languages. Seamlessly join, group, aggregate, and
order your distributed in-memory and on-disk data:
</p>
<div class="forntcodes__innertabs jsTabWrap">
<div class="nativecode__tabctrls flexi"><a class="nativecode__link active" href="#" data-tablink="sqlTabSQL">SQL</a></div>
<div class="nativecode__tabs">
<div class="nativecode__tab active" data-tab="sqlTabSQL">
<pre class="nativecode__codebox"> <code class="sql">SELECT country.name, city.name, MAX(city.population) as max_pop
FROM country JOIN city ON city.countrycode = country.code
WHERE country.code IN ('USA','BRA','ESP','JPN')
GROUP BY country.name, city.name
ORDER BY max_pop DESC LIMIT 3;</code></pre>
</div>
</div>
<div class="forntcodes__bottom"><a class="button" href="/features/sql.html">Learn More About Distributed SQL</a></div>
</div>
<!-- /.forntcodes__innertabs-->
</div>
<!-- /.forntcodes__tab2 (END Distributed SQL)-->
<div class="forntcodes__tab" data-ftab="frontcode-3">
<p class="forntcodes__tabtitle fz20 pb-1">ACID Transactions</p>
<p>Ignite can operate in a strongly consistent mode that provides full support for distributed ACID transactions. Transact across multiple cluster nodes, caches, tables, and partitions:</p>
<div class="forntcodes__innertabs jsTabWrap">
<div class="nativecode__tabctrls flexi"><a class="nativecode__link active" href="#" data-tablink="acidTabJava">Java</a><a class="nativecode__link" href="#" data-tablink="acidTabSharp">C#/.NET</a></div>
<div class="nativecode__tabs">
<div class="nativecode__tab active" data-tab="acidTabJava">
<pre class="nativecode__codebox"> <code class="java">IgniteTransactions transactions = ignite.transactions();
try (Transaction tx = transactions.txStart()) {
Integer hello = cache.get("Hello");
if (hello == 1)
cache.put("Hello", 11);
cache.put("World", 22);
tx.commit();
}</code></pre>
</div>
<div class="nativecode__tab" data-tab="acidTabSharp">
<pre class="nativecode__codebox"> <code class="csharp">var transactions = ignite.GetTransactions();
using (var tx = transactions.TxStart()) {
int hello = cache.Get("Hello");
if (hello == 1) {
cache.Put("Hello", 11);
}
cache.Put("World", 22);
tx.Commit();
}</code></pre>
</div>
</div>
<div class="forntcodes__bottom"><a class="button" href="/features/acid-transactions.html">Learn More About Transactions</a></div>
</div>
<!-- /.forntcodes__innertabs-->
</div>
<!-- /.forntcodes__tab3 (END ACID Transactions)-->
<div class="forntcodes__tab" data-ftab="frontcode-4">
<p class="forntcodes__tabtitle fz20 pb-1">Compute APIs In Java, Scala, Kotlin, C#, C++</p>
<p>
With traditional databases, for in-place calculations, you use stored procedures that are written in a language such as PL/SQL. With Ignite, you use modern JVM languages, C# or C++ to develop and execute custom tasks across
your distributed database:
</p>
<div class="forntcodes__innertabs jsTabWrap">
<div class="nativecode__tabctrls flexi"><a class="nativecode__link active" href="#" data-tablink="compTabJava">Java</a><a class="nativecode__link" href="#" data-tablink="compTabSharp">C#/.NET</a></div>
<div class="nativecode__tabs">
<div class="nativecode__tab active" data-tab="compTabJava">
<pre class="nativecode__codebox"> <code class="java">// Broadcast the task to server nodes only.
IgniteCompute compute = ignite.compute(ignite.cluster().forServers());
// Each remote server node will execute the logic of the task/lambda below.
compute.broadcast(() -> System.out.println(
"Hello Node: " + ignite.cluster().localNode().id()));</code></pre>
</div>
<div class="nativecode__tab" data-tab="compTabSharp">
<pre class="nativecode__codebox"> <code class="csharp">// Broadcast the task to server nodes only.
var compute = ignite.GetCluster().ForServers().GetCompute();
// Each remote server node will execute the custom PrintNodeIdAction task.
compute.Broadcast(new PrintNodeIdAction());</code></pre>
</div>
</div>
<div class="forntcodes__bottom"><a class="button" href="/features/compute-apis.html">Learn More About Compute APIs</a></div>
</div>
<!-- /.forntcodes__innertabs-->
</div>
<!-- /.forntcodes__tab4 (END Compute APIs)-->
<div class="forntcodes__tab" data-ftab="frontcode-5">
<p class="forntcodes__tabtitle fz20 pb-1">Built-In Machine Learning</p>
<p>
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:
</p>
<div class="forntcodes__innertabs jsTabWrap">
<div class="nativecode__tabctrls flexi"><a class="nativecode__link active" href="#" data-tablink="machineTabJava">Java</a></div>
<div class="nativecode__tabs">
<div class="nativecode__tab active" data-tab="machineTabJava">
<pre class="nativecode__codebox"> <code class="java">// Create the trainer
KNNClassificationTrainer trainer = new KNNClassificationTrainer()
.withK(3).withIdxType(SpatialIndexType.BALL_TREE)
.withDistanceMeasure(new EuclideanDistance())
.withWeighted(true);
// Train the model
KNNClassificationModel knnMdl = trainer.fit(ignite, dataCache, vectorizer);
// Make a prediction
double prediction = knnMdl.predict(observation);</code></pre>
</div>
</div>
<div class="forntcodes__bottom"><a class="button" href="/features/machinelearning.html">Learn More About Machine Learning</a></div>
</div>
<!-- /.forntcodes__innertabs-->
</div>
<!-- /.forntcodes__tab5 (END Machine Learning)-->
<div class="forntcodes__tab" data-ftab="frontcode-6">
<p class="forntcodes__tabtitle fz20 pb-1">Continuous Queries</p>
<p>
With relational databases, you use triggers to react to certain events. With Ignite, you deploy continuous queries that are written in a modern programming language such as Java or C# and process streams of changes on the
database and application side:
</p>
<div class="forntcodes__innertabs jsTabWrap">
<div class="nativecode__tabctrls flexi"><a class="nativecode__link active" href="#" data-tablink="contTabJava">Java</a><a class="nativecode__link" href="#" data-tablink="contTabSharp">C#/.NET</a></div>
<div class="nativecode__tabs">
<div class="nativecode__tab active" data-tab="contTabJava">
<pre class="nativecode__codebox"> <code class="java">ContinuousQuery qry = new ContinuousQuery<>();
// The callback that will be triggered on the application side.
qry.setLocalListener(new MyLocalListener());
// The callback that will be executed on the server side.
qry.setRemoteFilterFactory(new MyRemoteFilterFactory());
// Deploy the query in the cluster.
cache.query(query);</code></pre>
</div>
<div class="nativecode__tab" data-tab="contTabSharp">
<pre class="nativecode__codebox"> <code class="csharp">var cache = ignite.GetOrCreateCache("myCache");
var query = new ContinuousQuery(
new MyLocalListener(), // Will be triggered on the application side.
new MyRemoteFilter()); // Will be executed on the server side.
// Deploy the query in the cluster.
var handle = cache.QueryContinuous(query);</code></pre>
</div>
</div>
<div class="forntcodes__bottom"><a class="button" href="https://ignite.apache.org/docs/latest/key-value-api/continuous-queries" target="_blank">Learn More About Continuous Queries</a></div>
</div>
<!-- /.forntcodes__innertabs-->
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<!-- /.forntcodes__tab6 (END Continuous Queries)-->
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<h2 class="h3">New To Ignite? <br />Three Primary Usage Scenarios</h2>
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<article class="frontsimplecard cardsimple">
<h4 class="cardsimple__title">Application Acceleration <br />& Scale Out</h4>
<div class="cardsimple__text cardsimple__text--long">
Accelerate your existing applications by 100x using Ignite as an in-memory cache or in-memory data grid that is deployed over one or more external databases.
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<article class="frontsimplecard cardsimple">
<h4 class="cardsimple__title">Distributed Database For <br />HTAP Workloads</h4>
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</article>
<article class="frontsimplecard cardsimple">
<h4 class="cardsimple__title">Digital Integration Hub<br /> </h4>
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