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| href="#feat-vtab-c-multitier" role="tab" aria-controls="feat-vtab-c-multitier" |
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| <span>Co-located Compute</span> |
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| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'machine_learning'});" |
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| <span>Continuous Queries</span> |
| </a> |
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| |
| |
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| <!-- Tabs content --> |
| <div class="tab-content" id="v-pills-tabContent" role="tablist"> |
| |
| <div class="tab-pane active show card" id="feat-vtab-c-sql" role="tabpanel" |
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| <h3><a class="collapse" data-toggle="collapse" href="#feat-vtab-cb-sql" |
| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'distributed_sql'});" |
| aria-expanded="false" aria-controls="feat-vtab-cb-sql"> |
| <svg> |
| <use xlink:href="#index-icons--Database"></use> |
| </svg> |
| <span class="d-block">Distributed SQL</span> |
| </a></h3> |
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| |
| <div id="feat-vtab-cb-sql" class="collapse show" data-parent="#v-pills-tabContent" |
| role="tabpanel" aria-labelledby="feat-vtab-ch-sql"> |
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| |
| <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="code-tabs"> |
| <ul class="nav nav-tabs"> |
| <li class="nav-item"> |
| <a class="nav-link active" data-toggle="tab" href="#sql">SQL</a> |
| </li> |
| </ul> |
| |
| <!-- Tab panes --> |
| <div class="tab-content"> |
| <div class="tab-pane active" id="sql"> |
| <pre class="language-sql"> |
| <code> |
| 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> |
| |
| |
| <a href="/docs/latest/SQL/sql-introduction" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_features', 'event_label': 'sql'});" |
| title="Apache Ignite Distributed SQL" aria-label="Distributed SQL" |
| class="btn btn-secondary">Start Using SQL</a> |
| </div> |
| </div> |
| </div> |
| |
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| aria-labelledby="feat-vtab-multitier"> |
| <div class="card-header" role="tab" id="feat-vtab-ch-multitier"> |
| <h3><a class="collapsed" data-toggle="collapse" href="#feat-vtab-cb-multitier" aria-expanded="true" |
| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'multi_tier_storage'});" |
| aria-controls="feat-vtab-cb-multitier"> |
| <svg> |
| <use xlink:href="#index-icons--Distributed-IMDataStore"></use> |
| </svg> |
| <span class="d-block">Multi-Tier Storage</span></a></h3> |
| </div> |
| <div id="feat-vtab-cb-multitier" class="collapse" data-parent="#v-pills-tabContent" |
| role="tabpanel" aria-labelledby="feat-vtab-ch-multitier"> |
| <div class="card-body"> |
| |
| <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="code-tabs"> |
| <ul class="nav nav-tabs"> |
| <li class="nav-item"> |
| <a class="nav-link active" data-toggle="tab" |
| href="#storage-xml">XML</a> |
| </li> |
| <li class="nav-item"> |
| <a class="nav-link" data-toggle="tab" href="#storage-java">Java</a> |
| </li> |
| <li class="nav-item"> |
| <a class="nav-link" data-toggle="tab" |
| href="#storage-csharp">C#/.NET</a> |
| </li> |
| </ul> |
| |
| <!-- Tab panes --> |
| <div class="tab-content"> |
| <div class="tab-pane active" id="storage-xml"> |
| <pre class="language-xml"> |
| <code> |
| <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="tab-pane " id="storage-java"> |
| <pre class="language-java"> |
| <code> |
| 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="tab-pane " id="storage-csharp"> |
| <pre class="language-csharp"> |
| <code> |
| var cfg = new IgniteConfiguration |
| { |
| DataStorageConfiguration = new DataStorageConfiguration |
| { |
| DefaultDataRegionConfiguration = new DataRegionConfiguration |
| { |
| Name = "Default_Region", |
| PersistenceEnabled = true |
| } |
| } |
| }; |
| </code> |
| </pre> |
| </div> |
| </div> |
| </div> |
| |
| <a href="/docs/latest/memory-architecture" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_features', 'event_label': 'multi_tier_storage'});" |
| title="Apache Ignite Multi-Tier Storage" |
| aria-label="Apache Ignite Multi-Tier Storage" |
| class="btn btn-secondary">Learn More About Storage Engine</a> |
| </div> |
| </div> |
| </div> |
| |
| |
| |
| <div class="tab-pane card " id="feat-vtab-c-colocated" role="tabpanel" |
| aria-labelledby="feat-vtab-colocated"> |
| <div class="card-header" role="tab" id="feat-vtab-ch-colocated"> |
| <h3><a class="collapsed" data-toggle="collapse" href="#feat-vtab-cb-colocated" |
| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'colocated_compute'});" |
| aria-expanded="false" aria-controls="feat-vtab-cb-colocated"> |
| <svg> |
| <use xlink:href="#index-icons--Compute"></use> |
| </svg> |
| <span class="d-block d-md-none">Co-located Compute</span> |
| <span class="d-none d-md-block">Co-located Compute in Java, Scala, Kotlin, C#, C++</span> |
| </a></h3> |
| </div> |
| |
| <div id="feat-vtab-cb-colocated" class="collapse" data-parent="#v-pills-tabContent" |
| role="tabpanel" aria-labelledby="feat-vtab-ch-colocated"> |
| <div class="card-body"> |
| <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="code-tabs"> |
| <ul class="nav nav-tabs"> |
| <li class="nav-item"> |
| <a class="nav-link active" data-toggle="tab" href="#compute-java">Java</a> |
| </li> |
| <li class="nav-item"> |
| <a class="nav-link" data-toggle="tab" |
| href="#compute-csharp">C#/.NET</a> |
| </li> |
| </ul> |
| |
| <!-- Tab panes --> |
| <div class="tab-content"> |
| <div class="tab-pane active" id="compute-java"> |
| <pre class="language-java"> |
| <code> |
| // 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="tab-pane" id="compute-csharp"> |
| <pre class="language-csharp"> |
| <code> |
| // 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> |
| |
| <a href="/docs/latest/distributed-computing/distributed-computing" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_features', 'event_label': 'co_located_processsing'});" |
| title="Apache Ignite Co-located Processing" |
| aria-label="Apache Ignite Co-located Processing" |
| class="btn btn-secondary">Start Using Compute APIs</a> |
| </div> |
| </div> |
| </div> |
| |
| <div class="tab-pane card " id="feat-vtab-c-acid" role="tabpanel" |
| aria-labelledby="feat-vtab-acid"> |
| <div class="card-header" role="tab" id="feat-vtab-ch-acid"> |
| <h3><a class="collapsed" data-toggle="collapse" href="#feat-vtab-cb-acid" |
| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'acid_transactions'});" |
| aria-expanded="false" aria-controls="feat-vtab-cb-acid"> |
| <svg> |
| <use xlink:href="#index-icons--ACID"></use> |
| </svg> |
| <span class="d-block">ACID Transactions</span> |
| </a></h3> |
| </div> |
| |
| <div id="feat-vtab-cb-acid" class="collapse" data-parent="#v-pills-tabContent" |
| role="tabpanel" aria-labelledby="feat-vtab-ch-acid"> |
| <div class="card-body"> |
| <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="code-tabs"> |
| <ul class="nav nav-tabs"> |
| <li class="nav-item"> |
| <a class="nav-link active" data-toggle="tab" |
| href="#transactions-java">Java</a> |
| </li> |
| <li class="nav-item"> |
| <a class="nav-link" data-toggle="tab" |
| href="#transactions-csharp">C#/.NET</a> |
| </li> |
| </ul> |
| |
| <!-- Tab panes --> |
| <div class="tab-content"> |
| <div class="tab-pane active" id="transactions-java"> |
| <pre class="language-java"> |
| <code> |
| 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="tab-pane" id="transactions-csharp"> |
| <pre class="language-csharp"> |
| <code> |
| 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> |
| |
| <a href="/features/acid-transactions.html" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_features', 'event_label': 'transactions'});" |
| title="Apache Ignite ACID Transactions" |
| aria-label="Apache Ignite ACID Transactions" |
| class="btn btn-secondary">Learn More About Transactions</a> |
| </div> |
| </div> |
| </div> |
| |
| <div class="tab-pane card " id="feat-vtab-c-ml" role="tabpanel" |
| aria-labelledby="feat-vtab-ml"> |
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| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'machine_learning'});" |
| aria-expanded="false" aria-controls="feat-vtab-cb-ml"> |
| <svg> |
| <use xlink:href="#index-icons--Machine-Learning"></use> |
| </svg> |
| <span class="d-block d-md-none">Machine Learning</span> |
| <span class="d-none d-md-block">Built-In Machine Learning</span> |
| </a></h3> |
| </div> |
| <div id="feat-vtab-cb-ml" class="collapse" data-parent="#v-pills-tabContent" |
| role="tabpanel" aria-labelledby="feat-vtab-ch-ml"> |
| <div class="card-body"> |
| |
| <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="code-tabs"> |
| <ul class="nav nav-tabs"> |
| <li class="nav-item"> |
| <a class="nav-link active" data-toggle="tab" |
| href="#ml-java">Java</a> |
| </li> |
| </ul> |
| |
| <!-- Tab panes --> |
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| <div class="tab-pane active" id="ml-java"> |
| <pre class="language-java"> |
| <code> |
| // 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> |
| |
| <a href="/docs/latest/machine-learning/machine-learning" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_features', |
| 'event_label': 'machine_learning'});" |
| title="Apache Ignite Machine Learning" |
| aria-label="Apache Ignite Machine Learning" |
| class="btn btn-secondary">Start Using Ignite Machine Learning</a> |
| </div> |
| </div> |
| </div> |
| |
| <div class="tab-pane card " id="feat-vtab-c-conquery" role="tabpanel" |
| aria-labelledby="feat-vtab-conquery"> |
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| onclick="gtag('event', 'homepage_click', {'event_category':'features_section_tabs', 'event_label': 'continuous_queries'});" |
| aria-expanded="false" aria-controls="feat-vtab-cb-conquery"> |
| <svg style="padding: 6px;"> |
| <use xlink:href="#index-icons--continous-q"></use> |
| </svg> |
| <span class="d-block">Continuous Queries</span> |
| </a></h3> |
| </div> |
| <div id="feat-vtab-cb-conquery" class="collapse" data-parent="#v-pills-tabContent" |
| role="tabpanel" aria-labelledby="feat-vtab-ch-conquery"> |
| <div class="card-body"> |
| <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="code-tabs"> |
| <ul class="nav nav-tabs"> |
| <li class="nav-item"> |
| <a class="nav-link active" data-toggle="tab" href="#conquery-java">Java</a> |
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| <li class="nav-item"> |
| <a class="nav-link" data-toggle="tab" href="#conquery-csharp">C#/.NET</a> |
| </li> |
| </ul> |
| |
| <!-- Tab panes --> |
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| <div class="tab-pane active" id="conquery-java"> |
| <pre class="language-java"> |
| <code> |
| ContinuousQuery<Integer, String> 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="tab-pane" id="conquery-csharp"> |
| <pre class="language-csharp"> |
| <code> |
| var cache = ignite.GetOrCreateCache<int, string>("myCache"); |
| |
| var query = new ContinuousQuery<int, string>( |
| 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> |
| |
| <a href="/docs/latest/key-value-api/continuous-queries" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_features', |
| 'event_label': 'continuous_queries'});" |
| title="Apache Ignite Continuous Queries" |
| aria-label="Apache Ignite Continuous Queries" |
| class="btn btn-secondary">Start Using Continuous Queries</a> |
| </div> |
| </div> |
| </div> |
| </div> |
| </div> |
| </div> |
| |
| |
| </div> |
| |
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| </section> |
| |
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| |
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| <a href="https://ignite-summit.org/schedule/" target="_blank" rel="noopener" |
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| |
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| |
| |
| <section id="home-use-cases" class="section-block"> |
| |
| |
| <div class="container"> |
| <h2>How to <strong>Use</strong></h2> |
| |
| <div class="row"> |
| <div class="txt-wrapper"> |
| <h3>Applications Acceleration & Data Caching</h3> |
| <p> |
| 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. Think of a cache that you can |
| query with SQL, transact, and compute on. |
| </p> |
| |
| <a href="/use-cases/in-memory-data-grid.html" role="button" class="btn btn-primary" title="In-Memory Data Grid" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_use_cases', 'event_label': 'data_grid'});"> |
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| |
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| |
| </div> |
| |
| <div class="row"> |
| <div class="txt-wrapper"> |
| <h3>Database For Mixed Workloads</h3> |
| <p> |
| Build modern applications that support transactional and analytical workloads by using Ignite as |
| a database that scales beyond the available memory capacity. Ignite allocates memory for your hot |
| data and goes to disk whenever applications query cold records. |
| </p> |
| |
| <a href="/use-cases/in-memory-database.html" role="button" class="btn btn-primary" |
| aria-label="Learn More About In-Memory Database" title="In-Memory Database" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_use_cases', 'event_label': 'database'});"> |
| Learn More |
| </a> |
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| |
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| |
| <img class="lazyload" data-src="/images/svg-diagrams/home--unified-database--vertical.svg?20201221" |
| width="522" height="395" |
| alt="Distributed Database Diagram"/> |
| </div> |
| </div> |
| |
| <div class="row"> |
| |
| |
| <div class="txt-wrapper"> |
| <h3>High-Performance Computing</h3> |
| <p> |
| Execute kilobyte-size custom code over petabytes of data. Turn your Ignite database into a |
| distributed supercomputer for low-latency calculations, complex analytics, and machine learning. |
| </p> |
| |
| <a href="/use-cases/high-performance-computing.html" role="button" class="btn btn-primary" |
| aria-label="Learn More About High-Performance Computing" title="High-Performance Computin" |
| onclick="gtag('event', 'homepage_click', {'event_category':'apache_ignite_use_cases', 'event_label': 'high_performance_compute_cluster'});"> |
| Learn More |
| </a> |
| |
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| |
| <img class="lazyload" |
| width="546" height="388" |
| data-src="/images/svg-diagrams/home--high-perf-compute-cluster.svg?20201228" |
| alt="High-Performance Compute Cluster Diagram"/> |
| </div> |
| |
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| |
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