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DBMS > Heroic vs. MySQL vs. PostgreSQL

System Properties Comparison Heroic vs. MySQL vs. PostgreSQL

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonMySQL  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchWidely used open source RDBMSWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelTime Series DBMSRelational DBMS infoKey/Value like access via memcached APIRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#243  Overall
#14  Time Series DBMS
Score1215.14
Rank#2  Overall
#2  Relational DBMS
Score478.72
Rank#4  Overall
#4  Relational DBMS
Websitespotify.github.io/­heroic/­#!/­indexwww.mysql.comwww.postgresql.org
Technical documentationspotify.github.io/­heroic/­#!/­docs/­overviewdev.mysql.com/­docwww.postgresql.org/­docs/­manuals
DeveloperSpotifyOracle infosince 2010, originally MySQL AB, then SunPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release201419951989 info1989: Postgres, 1996: PostgreSQL
Current release8.0.15, February 201911.2, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoBSD
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.
  • Azure Database for MySQL: A fully managed, scalable MySQL relational database with high availability and security built in at no extra cost
  • Google Cloud SQL: A fully-managed database service for the Google Cloud Platform
  • Azure Database for PostgreSQL: A fully managed, scalable PostgreSQL relational database with high availability and security built in at no extra cost
  • Google Cloud SQL: A fully-managed database service for the Google Cloud Platform
Implementation languageJavaC and C++C
Server operating systemsFreeBSD
Linux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeyesyes
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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsyes infostandard with numerous extensions
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary native API
ADO.NET
JDBC
ODBC
native C library
streaming API for large objects
ADO.NET
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes infoproprietary syntaxuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyesMaster-master replication
Master-slave replication
Master-slave replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyes
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.noyesno
User concepts infoAccess controlUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources
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PGCon 2019, PostgreSQL Conference for Users and Developers
Ottawa, Canada, 28-31 May 2019

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Achieving High Availability with PostgreSQL
Webinar, 4PM UTC, 26 February 2019 (finished)

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