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DBMS > Databend vs. PostgreSQL vs. Realm vs. Splice Machine

System Properties Comparison Databend vs. PostgreSQL vs. Realm vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonPostgreSQL  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
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.Document storeRelational 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
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.postgresql.orgrealm.iosplicemachine.com
Technical documentationdocs.databend.comwww.postgresql.org/­docsrealm.io/­docssplicemachine.com/­how-it-works
DeveloperDatabend LabsPostgreSQL Global Development Group infowww.postgresql.org/­developerRealm, acquired by MongoDB in May 2019Splice Machine
Initial release20211989 info1989: Postgres, 1996: PostgreSQL20142014
Current release1.0.59, April 202316.3, May 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageRustCJava
Server operating systemshosted
Linux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnoyesyesyes
SQL infoSupport of SQLyesyes infostandard with numerous extensionsnoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no inforuns within the applications so server-side scripts are unnecessaryyes infoJava
Triggersnoyesyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and (since PostgreSQL 11) by hashnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoIn-Memory realmyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standard

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DatabendPostgreSQLRealmSplice Machine
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