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DBMS > Apache Phoenix vs. Datomic vs. Postgres-XL vs. Spark SQL vs. Transbase

System Properties Comparison Apache Phoenix vs. Datomic vs. Postgres-XL vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#131  Overall
#63  Relational DBMS
Score2.08
Rank#132  Overall
#64  Relational DBMS
Score0.56
Rank#253  Overall
#115  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.20
Rank#327  Overall
#144  Relational DBMS
Websitephoenix.apache.orgwww.datomic.comwww.postgres-xl.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationphoenix.apache.orgdocs.datomic.comwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationCognitectApache Software FoundationTransaction Software GmbH
Initial release201420122014 infosince 2012, originally named StormDB20141987
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 202310 R1, October 20183.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoMozilla public licenseOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureCScalaC and C++
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
macOS
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyesyes
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.nonoyes infoXML type, but no XML query functionalitynono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoyes infodistributed, parallel query executionSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyes infoTransaction Functionsuser defined functionsnoyes
TriggersnoBy using transaction functionsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peershorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoMVCCnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes 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.yesyes inforecommended only for testing and developmentnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynofine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Apache PhoenixDatomicPostgres-XLSpark SQLTransbase
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