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| <title>Distributed ANSI SQL - Apache Ignite</title> |
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| content="Apache Ignite comes with a ANSI-99 compliant, horizontally scalable, and fault-tolerant SQL engine that |
| allows you to interact with Ignite as with a regular SQL database."/> |
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| <h1>Distributed ANSI SQL <strong>With JOINs</strong></h1> |
| </div> |
| </header> |
| <div class="container"> |
| <p> |
| Apache Ignite® comes with a ANSI-99 compliant, horizontally scalable, and fault-tolerant SQL engine |
| that allows you to interact with Ignite as with a regular SQL database using JDBC, ODBC drivers, or |
| native SQL APIs available for Java, C#, C++, Python, and other programming languages. |
| </p> |
| <img class="img-responsive diagram-right" alt="SQL Database diagram" src="/images/svg-diagrams/distributed_sql.svg" alt="Distributed ANSI SQL With JOINs" /> |
| <p> |
| Ignite supports all DML commands, including SELECT, UPDATE, INSERT, and DELETE queries as well |
| as a subset of DDL commands relevant for distributed systems. |
| </p> |
| |
| <h2>SQL Joins</h2> |
| <p> |
| Ignite fully supports distributed joins for advanced querying needs. A distributed join is a SQL statement |
| with a join clause that combines two or more tables. If the tables are joined on the partitioning column |
| (affinity or primary key), the join is called a co-located join. Otherwise, if the tables were not |
| co-located initially, then Ignite does the join in a non-colocated fashion. Co-located joins avoid data |
| shuffling between nodes and minimize network usage, thus, performing much faster than a non-colocated |
| counterpart. |
| </p> |
| |
| <h2>SQL and In-Memory Mode</h2> |
| <p> |
| Apache Ignite can function in a pure in-memory mode when all the data and indexes are located solely in |
| memory. In this mode, Ignite SQL shows the highest performance since all the data is served from memory |
| with no usage of the disk tier at all. |
| </p> |
| |
| <h2>SQL and Native Persistence</h2> |
| <p> |
| In this mode, Ignite persists 100% of data and indexes in the native persistence while caching as much |
| as possible in memory. Ignite SQL engine does not require to cache an entire data set in memory to |
| operate correctly. If the engine finds that a record is not cached, then it will read the record from |
| disk. Your application only executes SQL queries, and Ignite gets the records from both memory and disk |
| automatically. |
| </p> |
| <p> |
| On cluster restarts, Ignite reads data and indexes from disk, eliminating the need for memory warm-up, |
| which significantly decreases the time of any potential downtimes. |
| |
| </p> |
| |
| <h2>SQL and 3rd Party Databases</h2> |
| <p> |
| Ignite can be used as a caching layer for external databases such as RDBMS, NoSQL, or Hadoop. In this mode, |
| the Ignite SQL engine requires caching all the data needed for SQL queries in memory since the engine |
| currently does not support federated queries. |
| </p> |
| |
| <p> |
| If federated queries between Ignite and an external database are required, then you can consider Ignite |
| integration for Spark, where the DataFrames API can join the data stored in Ignite and other systems. |
| </p> |
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| <hr class="my-4"> |
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| <div class="col-sm-6"> |
| <ul> |
| <li> |
| <p><a href="https://apacheignite-sql.readme.io/docs/how-ignite-sql-works" target="docs">Ignite SQL implementation details <i class="fa fa-angle-double-right"></i></a></p> |
| </li> |
| <li> |
| <p><a href="https://apacheignite-sql.readme.io/docs/distributed-joins" target="docs">Distributed JOINs <i class="fa fa-angle-double-right"></i></a></p> |
| </li> |
| <li> |
| <p><a href="https://apacheignite-sql.readme.io/docs/sql-reference-overview" target="docs">SQL Reference <i class="fa fa-angle-double-right"></i></a></p> |
| </li> |
| </ul> |
| </div> |
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| <ul> |
| <li> |
| <p><a href="/use-cases/spark-acceleration.html">Apache Ignite and Spark <i class="fa fa-angle-double-right"></i></a></p> |
| </li> |
| <li> |
| <p><a href="/arch/multi-tier-storage.html">Multi-Tier Storage <i class="fa fa-angle-double-right"></i></a></p> |
| </li> |
| </ul> |
| </div> |
| </div> |
| </div> |
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