DBMS > Infobright vs. PostgreSQL vs. Spark SQL
System Properties Comparison Infobright vs. PostgreSQL vs. Spark SQL
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|Editorial information provided by DB-Engines|
|Name||Infobright Xexclude from comparison||PostgreSQL Xexclude from comparison||Spark SQL Xexclude from comparison|
|Description||High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend||Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL||Spark SQL is a component on top of 'Spark Core' for structured data processing|
|Primary database model||Relational DBMS||Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.||Relational DBMS|
|Secondary database models||Document store|
|Developer||Ignite Technologies Inc.; formerly InfoBright Inc.||PostgreSQL Global Development Group www.postgresql.org/developer||Apache Software Foundation|
|Initial release||2005||1989 1989: Postgres, 1996: PostgreSQL||2014|
|Current release||12.0, October 2019||v2.4.4, September 2019|
|License Commercial or Open Source||commercial The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016||Open Source BSD||Open Source Apache 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
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|Server operating systems||Linux|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||yes specific XML-type available, but no XML query functionality.||no|
|Secondary indexes||no Knowledge Grid Technology used instead||yes||no|
|SQL Support of SQL||yes||yes standard with numerous extensions||SQL-like DML and DDL statements|
|APIs and other access methods||ADO.NET|
native C library
streaming API for large objects
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||no||user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.||no|
|Partitioning methods Methods for storing different data on different nodes||none||partitioning by range, list and (since PostgreSQL 11) by hash||yes, utilizing Spark Core|
|Replication methods Methods for redundantly storing data on multiple nodes||Master-slave replication||Master-slave replication other methods possible by using 3rd party extensions||none|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||no||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes||no||no|
|User concepts Access control||fine grained access rights according to SQL-standard exploiting MySQL or PostgreSQL frontend capabilities||fine grained access rights according to SQL-standard||no|
More information provided by the system vendor
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