ignite.apache.orgDistributed Database - Apache Ignite

Close Quick Start Learning resources Training and Courses FAQ Use Cases In-Memory Cache In-Memory Data Grid In-Memory Database Key-Value Store High Performance Computing Digital Integration Hub Spark Acceleration Hadoop Acceleration View All Features Multi-Tier Storage Native Persistence Distributed SQL Key-Value APIs ACID Transactions Compute APIs Services Machine Learning Real-Time Streaming APIs Messaging Continuous Queries View All Community Project Info Events Powered by Resources Blog Docs Download Ignite 2.16 Ignite Summit 2023 — Watch on demand — Register now! Download Ignite 2.16.0 Get Started Features Community Powered By Resources Docs Quick Start Guide Learning resources Training and Courses FAQ USE CASES In-Memory Cache In-Memory Data Grid In-Memory Database Key-Value Store High-Performance Computing Digital Integration Hub Spark Acceleration Hadoop Acceleration View all MULTI-TIER STORAGE Multi-Tier Storage Native Persistence ESSENTIAL Developer APIs Distributed SQL Key-Value APIs ACID Transactions High-Performance Computing APIs Compute APIs Services Machine Learning Real-Streaming APIs Real-Time Streaming APIs Messaging Continuous Queries View all Project Info Apache Ignite Story Meet The Community Start Contributing Ask Questions Events Apache Ignite Summit Meetups Upcoming Events Past Events Blog Technical resources Learning resources Training and Courses Apache Ignite Book Mailing Lists, Forums And Discussion Archives FAQ Distributed Database For High‑Performance Applications With In‑Memory Speed Scale Across Memory And Disk Without Compromise Start Coding A top-5 project of the Apache Software Foundation Big Data Users Lists Users Lists Dev Lists Leading companies around the world select Ignite to speed up and scale applications used by millions of people daily Use Ignite Core Capabilities To Start Easily And Scale Faster Multi-Tier Storage Distributed SQL ACID Transactions Compute APIs Machine Learning Continuous Queries View all features Multi-Tier Storage 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: XML Java C#/.NET bean property name="dataStorageConfiguration" bean property name="defaultDataRegionConfiguration" bean property name="persistenceEnabled" value="true"/ /bean /property /bean /property /bean IgniteConfiguration cfg = new IgniteConfiguration(); DataStorageConfiguration storageCfg = new DataStorageConfiguration(); // Enable Ignite Persistence storageCfg.getDefaultDataRegionConfiguration().setPersistenceEnabled(true); // Using the new storage configuration cfg.setDataStorageConfiguration(storageCfg); var cfg = new IgniteConfiguration { DataStorageConfiguration = new DataStorageConfiguration { DefaultDataRegionConfiguration = new DataRegionConfiguration { Name = "Default_Region", PersistenceEnabled = true } } }; Learn More About Multi-Tier Storage Distributed SQL 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: 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; Learn More About Distributed SQL ACID Transactions 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: Java C#/.NET 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(); } 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(); } Learn More About Transactions Compute APIs In Java, Scala, Kotlin, C#, C++ 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: Java C#/.NET // 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())); // 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()); Learn More About Compute APIs Built-In Machine Learning 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: 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); Learn More About Machine Learning Continuous Queries 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: Java C#/.NET 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); 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); Learn More About Continuous Queries New To Ignite? Three Primary Usage Scenarios Application Acceleration & Scale Out 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. Distributed Database For HTAP Workloads Build applications that support transactional and analytical workloads by using Ignite as a database that scales beyond available memory capacity. Digital Integration Hub Create an advanced platform architecture that aggregates multiple back-end systems and databases into a low-latency and shared data store. Learn More Ignite User Stories Software & SaaS Banking & Finances Retail Biotech Logistics & Transportation Others Real-time Data Access with Apache Ignite SQL Improving the CERN Control and Monitoring Platform (C2MON) with Apache Ignite How nference.ai leverages Ignite for distributed analytics in the bioinformatics domain Leveraging In Memory Compute Grids With Core Systems Of Record Apache Ignite, Load Reduction and System Scaling for Banking S9D Using Apache...