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DBMS > Datomic vs. Hypertable vs. PostgreSQL vs. Spark SQL

System Properties Comparison Datomic vs. Hypertable vs. PostgreSQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHypertable  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn open source BigTable implementation based on distributed file systems such as HadoopWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeRelational 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 store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comwww.postgresql.orgspark.apache.org/­sql
Technical documentationdocs.datomic.comwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectHypertable Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release201220091989 info1989: Postgres, 1996: PostgreSQL2014
Current release1.0.6735, June 20230.9.8.11, March 201616.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU version 3. Commercial license availableOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++CScala
Server operating systemsAll OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.no
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesno
SQL infoSupport of SQLnonoyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIC++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesClojure
Java
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
TriggersBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factor on file system levelSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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More resources
DatomicHypertablePostgreSQLSpark SQL
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