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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
NameApache Impala  Xexclude from comparisonPostgreSQL  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score634.91
Rank#4  Overall
#4  Relational DBMS
Score1.17
Rank#185  Overall
#85  Relational DBMS
Websiteimpala.apache.orgwww.postgresql.orgvitess.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.org/­docsvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group infowww.postgresql.org/­developerThe Linux Foundation, PlanetScale
Initial release20131989 info1989: Postgres, 1996: PostgreSQL2013
Current release4.1.0, June 202216.2, February 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSDOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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.
Implementation languageC++CGo
Server operating systemsLinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Docker
Linux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard with numerous extensionsyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoproprietary syntax
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache ImpalaPostgreSQLVitess
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