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| in-memory and on-disk and supports key-value, SQL, and processing APIs"/> |
| <title>In-Memory Data Grid - Apache Ignite</title> |
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| <body> |
| <div id="wrapper"> |
| <!--#include virtual="/includes/header.html" --> |
| |
| <main id="main" role="main" class="container"> |
| <section id="datagrid" class="page-section"> |
| <h1 class="first">Key-Value In-Memory Data Grid</h1> |
| <div class="col-sm-12 col-md-12 col-xs-12" style="padding:0 0 20px 0;"> |
| <div class="col-sm-6 col-md-6 col-xs-12" style="padding-left:0; padding-right:0"> |
| <p> |
| Ignite provides extensive and rich key-value APIs and can act as an in-memory data grid. |
| You can think of Ignite as of a distributed partitioned hash map with every |
| cluster node owning a portion of the overall data set. Unlike other in-memory data grids (IMDG), |
| Ignite enables storing data both, in memory and on disk, and |
| therefore is able to store more data than can fit in the physical memory. |
| </p> |
| <p> |
| Ignite data grid is one of the fastest implementations of ACID transactions or |
| atomic data updates in distributed clusters today. We know it because we constantly benchmark it ourselves. |
| </p> |
| </div> |
| <div class="col-sm-4 col-md-6 col-xs-12" style="padding-right:0"> |
| <img class="img-responsive" src="/images/data_grid.png" width="500px" style="float:right;"/> |
| </div> |
| </div> |
| |
| <div class="page-heading">3rd Party Databases</div> |
| <p> |
| Inite in-memory data grid can improve performance and scalability of existing 3rd party databases, like RDBMS, |
| NoSQL, or Hadoop-based storages, by sliding in as a distribute cache between the application and database layers. This approach does not require |
| rip-and-replace of the existing data, and will automatically write-through or read-through all the updates |
| or reads to or from the underlying database. Ignite will automatically merge with the underlying database |
| transactions, providing transparent transactional behavior to the users. |
| </p> |
| <p> |
| However, this approach also has its limitations. For example, SQL or scan queries will only include the |
| results stored in memory, and not in the external database, since Ignite cannot index the external data. |
| If you require that data on disk should be indexed and accessible via SQL queries, we recommend that you look at |
| <a href="/arch/persistence.html">Ignite native persistence</a>. |
| </p> |
| |
| <div class="page-heading">JCache APIs</div> |
| <p> |
| Ignite key-value APIs comply with <a href="/use-cases/caching/jcache-provider.html">JCache (JSR 107)</a> |
| specification that supports the following: |
| </p> |
| <ul class="page-list"> |
| <li>In-Memory Key Value Store</li> |
| <li>Basic Cache Operations</li> |
| <li>ConcurrentMap APIs</li> |
| <li>Collocated Processing (EntryProcessor)</li> |
| <li>Events and Metrics</li> |
| <li>Pluggable Persistence</li> |
| </ul> |
| |
| <div class="page-heading">Extended Key-Value APIs</div> |
| <p> |
| In addition to the standard JCache API, Ignites supports distributed ACID transactions, |
| scan and continuous queries, collocated processing and more. |
| </p> |
| |
| <p> |
| The data grid has been built from the ground up to linearly scale to hundreds of nodes with strong |
| semantics for data locality and affinity data routing to reduce redundant data noise. It can be |
| viewed as a distributed partitioned hash map with every cluster node owning a portion of the |
| overall data. This way the more cluster nodes we add, the more data we can cache. |
| </p> |
| <div class="videos"> |
| <div class="page-heading">Videos</div> |
| <ul class="page-list"> |
| <li> |
| <i class="fa fa-lg fa-play-circle-o"></i> |
| <span class="video-title"> |
| <a target="youtube" href="https://www.youtube.com/watch?v=pFbDWpOiMOU">Getting Started with Data Grid</a> |
| </span> |
| <span class="video-duration">03:49</span> |
| </li> |
| </ul> |
| </div> |
| |
| <div class="code-examples"> |
| <div class="page-heading">Code Examples</div> |
| <!-- Nav tabs --> |
| <ul id="datagrid-examples" class="nav nav-tabs"> |
| <li class="active"><a href="#datagrid-example-basic" role="tab" data-toggle="tab">Put and Get</a></li> |
| <li><a href="#datagrid-example-transactions" role="tab" data-toggle="tab">Transactions</a></li> |
| <li><a href="#datagrid-example-locks" role="tab" data-toggle="tab">Locks</a></li> |
| <li><a href="#datagrid-example-sqlquery" role="tab" data-toggle="tab">SQL Query</a></li> |
| <li><a href="#datagrid-example-sqljoin" role="tab" data-toggle="tab">SQL Join</a></li> |
| <li><a href="#datagrid-example-sqlaggregation" role="tab" data-toggle="tab">SQL Aggregation</a></li> |
| </ul> |
| |
| <!-- Tab panes --> |
| <div class="tab-content"> |
| <div role="tabpanel" class="tab-pane active" id="datagrid-example-basic"> |
| <pre class="brush:java"> |
| Ignite ignite = Ignition.ignite(); |
| |
| // Get an instance of named cache. |
| final IgniteCache<Integer, String> cache = ignite.cache("cacheName"); |
| |
| // Store keys in cache. |
| for (int i = 0; i < 10; i++) |
| cache.put(i, Integer.toString(i)); |
| |
| // Retrieve values from cache. |
| for (int i = 0; i < 10; i++) |
| System.out.println("Got [key=" + i + ", val=" + cache.get(i) + ']'); |
| |
| // Remove objects from cache. |
| for (int i = 0; i < 10; i++) |
| cache.remove(i); |
| |
| // Atomic put-if-absent. |
| cache.putIfAbsent(1, "1"); |
| |
| // Atomic replace. |
| cache.replace(1, "1", "2"); |
| </pre> |
| </div> |
| <div role="tabpanel" class="tab-pane" id="datagrid-example-transactions"> |
| <pre class="brush:java"> |
| Ignite ignite = Ignition.ignite(); |
| |
| // Clone every object we get from cache, so we can freely update it. |
| IgniteCache<Integer, Account> cache = ignite.cache("cacheName"); |
| |
| try (IgniteTx tx = Ignition.ignite().transactions().txStart()) { |
| Account acct = cache.get(acctId); |
| |
| assert acct != null; |
| |
| // Deposit $20 into account. |
| acct.setBalance(acct.getBalance() + 20); |
| |
| // Store updated account in cache. |
| cache.put(acctId, acct); |
| |
| tx.commit(); |
| } |
| </pre> |
| </div> |
| <div role="tabpanel" class="tab-pane" id="datagrid-example-locks"> |
| <pre class="brush:java"> |
| Ignite ignite = Ignition.ignite(); |
| |
| // Get an instance of named cache. |
| final GridCache<String, Integer> cache = ignite.cache("cacheName"); |
| |
| // Lock cache key "Hello". |
| Lock lock = cache.lock("Hello"); |
| |
| lock.lock(); |
| |
| try { |
| cache.put("Hello", 11); |
| cache.put("World", 22); |
| } |
| finally { |
| lock.unlock(); |
| } |
| </pre> |
| </div> |
| <div role="tabpanel" class="tab-pane" id="datagrid-example-sqlquery"> |
| <pre class="brush:java"> |
| IgniteCache<Long, Person> cache = ignite.cache("mycache"); |
| |
| SqlFieldsQuery sql = new SqlFieldsQuery( |
| "select concat(firstName, ' ', lastName) from Person"); |
| |
| // Select concatinated first and last name for all persons. |
| try (QueryCursor<List<?>> cursor = cache.query(sql)) { |
| for (List<?> row : cursor) |
| System.out.println("Full name: " + row.get(0)); |
| } |
| </pre> |
| </div> |
| <div role="tabpanel" class="tab-pane" id="datagrid-example-sqljoin"> |
| <pre class="brush:java"> |
| IgniteCache<Long, Person> personCache = ignite.cache("personCache"); |
| |
| // Select with join between Person and Organization to |
| // get the names of all the employees of a specific organization. |
| SqlFieldsQuery sql = new SqlFieldsQuery( |
| "select p.name " |
| + "from Person p, \"orgCache\".Organization o where " |
| + "p.orgId = o.id " |
| + "and o.name = ?"); |
| |
| // Execute the query and obtain the query result cursor. |
| try (QueryCursor<List<?>> cursor = personCache.query(sql.setArgs("Ignite"))) { |
| for (List<?> row : cursor) |
| System.out.println("Person name=" + row); |
| } |
| </pre> |
| </div> |
| <div role="tabpanel" class="tab-pane" id="datagrid-example-sqlaggregation"> |
| <pre class="brush:java"> |
| IgniteCache<Long, Person> personCache = ignite.cache("personCache"); |
| |
| // Select average age of people working within different departments. |
| SqlFieldsQuery sql = new SqlFieldsQuery( |
| "select avg(p.age) as avg_age, d.name as dpmt_name, o.name as org_name " |
| + "from Person p, \"depCache\".Department d, \"orgCache\".Organization o " |
| + "where p.depid = d.id and d.orgid = o.id " |
| + "group by d.name, o.name " |
| + "order by avg_age"; |
| |
| // Execute the query and obtain the query result cursor. |
| try (QueryCursor<List<?>> cursor = personCache.query(sql.setArgs("Ignite"))) { |
| for (List<?> row : cursor) |
| System.out.println("Average age by department and organization: " + row); |
| } |
| </pre> |
| </div> |
| </div> |
| </div> |
| </section> |
| |
| <section id="key-features" class="page-section"> |
| <h2>More on Data Grid</h2> |
| <table class="formatted" name="key-value-apis"> |
| <thead> |
| <tr> |
| <th width="35%" class="left">Feature</th> |
| <th>Description</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr> |
| <td class="left">Key-Value Store</td> |
| <td> |
| <p> |
| Ignite data grid is a <code>key-value store</code> which can store data both, in-memory |
| and on-disk. It can be viewed as a distributed partitioned hash map, with every cluster |
| node owning a portion of the overall data. This way the more cluster nodes we add, |
| the more data we can store: |
| </p> |
| |
| <div class="page-links"> |
| <a href="/use-cases/database/key-value-store.html">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Durable Memory</td> |
| <td> |
| <p> |
| Ignite <code>Durable Memory</code> allows storing and processing data and indexes |
| both, in memory and on disk. The in-memory data, including indexes, is always |
| stored and managed <code>off-heap</code>, completely removing any type of Garbage |
| Collection overhead. |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/durable-memory" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">JCache (JSR 107)</td> |
| <td> |
| <p> |
| Ignite is a 100% compliant implementation of <span style="white-space: nowrap">JCache (JSR 107)</span> specification. |
| JCache provides a very simple to use, yet very powerful API for data caching: |
| </p> |
| <div class="page-links"> |
| <a href="/use-cases/caching/jcache-provider.html">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Memory-Centric Storage</td> |
| <td> |
| <p> |
| Apache Ignite is based on distributed <i>memory-centric architecture</i> that combines the |
| performance and scale of in-memory computing together with the disk durability and strong |
| consistency in one system: |
| </p> |
| <div class="page-links"> |
| <a href="/arch/memorycentric.html">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Collocated Processing</td> |
| <td> |
| <p> |
| Ignite allows executing any native Java, C++, and .NET/C# code directly on the server-side, |
| close to the data, in collocated fashion: |
| </p> |
| <div class="page-links"> |
| <a href="/features/collocatedprocessing.html" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Client-side Near Caches</td> |
| <td> |
| <p> |
| Near cache is local client-side cache that stores the most recently and most frequently accessed data. |
| </p> |
| <div class="page-links"> |
| <a href="http://apacheignite.readme.io/docs/near-caches" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">ACID Transactions</td> |
| <td> |
| <p> |
| Ignite provides fully ACID compliant distributed transactions that ensure guaranteed consistency. |
| </p> |
| <div class="page-links"> |
| <a href="/features/transactions.html">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left" width="35%">Deadlock-Free Transactions</td> |
| <td> |
| <p> |
| Ignite supports deadlock-free, optimistic transactions, which do not acquire any locks, |
| and free users from worrying about the lock order. |
| Such transactions also provide much better performance: |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/transactions" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left" width="35%">Transactional Entry Processor</td> |
| <td> |
| <p> |
| Ignite transactional entry processor allows executing collocated user logic on the server |
| side within a transaction: |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/affinity-collocation#ignitecompute-vs-entryprocessor" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left" width="35%">Cross-Partition Transactions</td> |
| <td> |
| <p> |
| In Ignite, transactions can be performed on all partitions of a cache across the whole |
| cluster: |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/transactions#ignitetransactions" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left" width="35%">Locks</td> |
| <td> |
| <p> |
| Ignite allows developers to define explicit locks enforcing mutual exclusion on cached objects: |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/distributed-locks" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left" width="35%">Continuous Queries</td> |
| <td> |
| <p> |
| Continuous queries are useful for cases when you want to execute a query and then |
| continue to get notified about the data changes that fall into your query filter: |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/continuous-queries" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left" width="35%">Write-Through</td> |
| <td> |
| <p> |
| Write-Through mode allows updating the data in the database. |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/3rd-party-store#read-through-and-write-through" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Read-Through</td> |
| <td> |
| <p> |
| Read-Through mode allows reading the data from the database. |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/3rd-party-store#read-through-and-write-through" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Write-Behind Caching</td> |
| <td> |
| <p> |
| Ignite provides an option to asynchronously perform updates to the database via Write-Behind Caching. |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite.readme.io/docs/3rd-party-store#section-write-behind-caching" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Hibernate L2 Caching</td> |
| <td> |
| <p> |
| Ignite data grid can be used as <code>Hibernate Second-Level Cache</code> (or L2 cache), |
| which can significantly speed-up the persistence layer of your application. |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite-mix.readme.io/docs/hibernate-l2-cache" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Spring Caching</td> |
| <td> |
| <p> |
| Ignite provides Spring-annotation-based way to enable caching for Java methods so that |
| the result of a method execution is stored in the Ignite cache. If later the same |
| method is called with the same set of parameters, the result will be retrieved from |
| the cache instead of actually executing the method. |
| </p> |
| <div class="page-links"> |
| <a href="http://apacheignite-mix.readme.io/docs/spring-caching" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">Spring Data</td> |
| <td> |
| <p> |
| Apache Ignite implements Spring Data <code>CrudRepository</code> interface that not only supports basic CRUD operations but also provides access to the Apache Ignite SQL capabilities via the unified Spring Data API. |
| </p> |
| <div class="page-links"> |
| <a href="https://apacheignite-mix.readme.io/docs/spring-data" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| <tr> |
| <td class="left">OSGI Support</td> |
| <td> |
| <p></p> |
| <div class="page-links"> |
| <a href="https://apacheignite-mix.readme.io/docs/starting-inside-an-osgi-container" target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a> |
| </div> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </section> |
| </main> |
| |
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