DBMS > GeoMesa vs. PostgreSQL vs. Spark SQL
System Properties Comparison GeoMesa vs. PostgreSQL vs. Spark SQL
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|Editorial information provided by DB-Engines|
|Name||GeoMesa Xexclude from comparison||PostgreSQL Xexclude from comparison||Spark SQL Xexclude from comparison|
|Description||GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.||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||Spatial 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|
Graph DBMS with Apache Age
Vector DBMS with pgvector extension
|Developer||CCRi and others||PostgreSQL Global Development Group www.postgresql.org/developer||Apache Software Foundation|
|Initial release||2014||1989 1989: Postgres, 1996: PostgreSQL||2014|
|Current release||4.0.2, July 2023||16.0, September 2023||3.4.1 ( 2.13), June 2023|
|License Commercial or Open Source||Open Source Apache License 2.0||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||FreeBSD|
|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|
|SQL Support of SQL||no||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||depending on storage layer||partitioning by range, list and (since PostgreSQL 11) by hash||yes, utilizing Spark Core|
|Replication methods Methods for redundantly storing data on multiple nodes||depending on storage layer||Source-replica replication other methods possible by using 3rd party extensions||none|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes||no|
|Consistency concepts Methods to ensure consistency in a distributed system||depending on storage layer||Immediate Consistency|
|Foreign keys Referential integrity||no||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||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.||depending on storage layer||no||no|
|User concepts Access control||yes depending on the DBMS used for storage||fine grained access rights according to SQL-standard||no|
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