DBMS > PostgreSQL vs. Stardog
System Properties Comparison PostgreSQL vs. Stardog
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|Editorial information provided by DB-Engines|
|Name||PostgreSQL Xexclude from comparison||Stardog Xexclude from comparison|
|Description||Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL||Semantic graph DBMS, developed in Java|
|Primary database model||Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.||Graph DBMS|
|Secondary database models||Document store|
|Developer||PostgreSQL Global Development Group www.postgresql.org/developer||Complexible Inc.|
|Initial release||1989 1989: Postgres, 1996: PostgreSQL||2010|
|Current release||11.2, February 2019||4.2.4, March 2017|
|License Commercial or Open Source||Open Source BSD||commercial Limited community edition free|
|Cloud-based only Only available as a cloud service||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||FreeBSD|
|All OS with a Java VM|
|Typing predefined data types such as float or date||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.||yes specific XML-type available, but no XML query functionality.||no Import/export of XML data possible|
|SQL Support of SQL||yes standard with numerous extensions||SPARQL is used as query language|
|APIs and other access methods||native C library|
streaming API for large objects
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.||no|
|Triggers||yes||yes via event handlers|
|Partitioning methods Methods for storing different data on different nodes||partitioning by range, list and (since PostgreSQL 11) by hash||none|
|Replication methods Methods for redundantly storing data on multiple nodes||Master-slave replication other methods possible by using 3rd party extensions||Master-master replication in HA-Cluster using Apache ZooKeeper|
|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 in HA-Cluster|
|Foreign keys Referential integrity||yes||yes relationships in graphs|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID|
|Concurrency Support for concurrent manipulation of data||yes||yes|
|Durability Support for making data persistent||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||yes|
|User concepts Access control||fine grained access rights according to SQL-standard||Access rights for users and roles|
More information provided by the system vendor
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|Related products and services|
|3rd parties||Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development.|
General SQL Parser: Instantly adding parsing, decoding, analysis and rewrite SQL processing capability to your products.
Azure Database for PostgreSQL provides fully managed, enterprise-ready community PostgreSQL database as a service
pgDash: In-Depth PostgreSQL Monitoring.
DBHawk: a web-based PostgreSQL/Greenplum database tool. Boost database development and BI productivity with an online Universal database tool.
2ndQuadrant: PostgreSQL Solutions for the Enterprise.
Dremio is like magic for PostgreSQL accelerating your analytical queries up to 1,000x.
We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
|DB-Engines blog posts|
PostgreSQL is the DBMS of the Year 2018
|Conferences and events|
PGCon 2019, PostgreSQL Conference for Users and Developers
Achieving High Availability with PostgreSQL
|Recent citations in the news|
Building a scalable PostgreSQL solution
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