DBMS > Apache Impala vs. PostgreSQL vs. Vitess
System Properties Comparison Apache Impala vs. PostgreSQL vs. Vitess
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|Editorial information provided by DB-Engines
|Apache Impala Xexclude from comparison
|PostgreSQL Xexclude from comparison
|Vitess Xexclude from comparison
|Analytic DBMS for Hadoop
|Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
|Scalable, distributed, cloud-native DBMS, extending MySQL
|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.
|Secondary database models
Graph DBMS with Apache Age
Vector DBMS with pgvector extension
|Apache Software Foundation Apache top-level project, originally developed by Cloudera
|PostgreSQL Global Development Group www.postgresql.org/developer
|The Linux Foundation, PlanetScale
|1989 1989: Postgres, 1996: PostgreSQL
|4.1.0, June 2022
|16.2, February 2024
|15.0.2, December 2022
|License Commercial or Open Source
|Open Source Apache Version 2
|Open Source BSD
|Open Source Apache Version 2.0, commercial licenses available
|Cloud-based only Only available as a cloud service
|DBaaS offerings (sponsored links) Database as a Service
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|Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
|PlanetScale: The easiest way to deploy Vitess in the cloud. Get the scalability of Vitess without all the work. Start your fully managed database with PlanetScale today.
|Server operating systems
|Typing predefined data types such as float or date
|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.
|SQL Support of SQL
|SQL-like DML and DDL statements
|yes standard with numerous extensions
|yes with proprietary extensions
|APIs and other access methods
native C library
streaming API for large objects
|Supported programming languages
|All languages supporting JDBC/ODBC
|Server-side scripts Stored procedures
|yes user defined functions and integration of map-reduce
|user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
|yes proprietary syntax
|Partitioning methods Methods for storing different data on different nodes
|partitioning by range, list and (since PostgreSQL 11) by hash
|Replication methods Methods for redundantly storing data on multiple nodes
|selectable replication factor
|Source-replica replication other methods possible by using 3rd party extensions
|MapReduce Offers an API for user-defined Map/Reduce methods
|yes query execution via MapReduce
|Consistency concepts Methods to ensure consistency in a distributed system
|Eventual Consistency across shards
Immediate Consistency within a shard
|Foreign keys Referential integrity
|yes not for MyISAM storage engine
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|ACID at shard level
|Concurrency Support for concurrent manipulation of data
|yes table locks or row locks depending on storage engine
|Durability Support for making data persistent
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|Access rights for users, groups and roles based on Apache Sentry and Kerberos
|fine grained access rights according to SQL-standard
|Users with fine-grained authorization concept no user groups or roles
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