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DBMS > FatDB vs. Ingres vs. OpenMLDB vs. PostgreSQL vs. Spark SQL

System Properties Comparison FatDB vs. Ingres vs. OpenMLDB vs. PostgreSQL vs. Spark SQL

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIngres  Xexclude from comparisonOpenMLDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Well established RDBMSAn open-source machine learning database that provides a feature platform for training and inferenceWidely 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 modelDocument store
Key-value store
Relational DBMSTime Series 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 modelsRelational DBMSDocument 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
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.02
Rank#367  Overall
#37  Time Series DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.actian.com/­databases/­ingresopenmldb.aiwww.postgresql.orgspark.apache.org/­sql
Technical documentationdocs.actian.com/­ingresopenmldb.ai/­docs/­zh/­mainwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudActian Corporation4 Paradigm Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release20121974 infooriginally developed at University Berkely in early 1970s20201989 info1989: Postgres, 1996: PostgreSQL2014
Current release11.2, May 20222024-2 February 202416.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#CC++, Java, ScalaCScala
Server operating systemsWindowsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
LinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeyesFixed schemayesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.no infobut tools for importing/exporting data from/to XML-files availablenoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryesyesyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
SQLAlchemy
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesC#C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyes infovia applicationsyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyhorizontal partitioningpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorIngres ReplicatorSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
FatDBIngresOpenMLDBPostgreSQLSpark SQL
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