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DBMS > AgensGraph vs. Apache Phoenix vs. PostGIS vs. Spark SQL

System Properties Comparison AgensGraph vs. Apache Phoenix vs. PostGIS vs. Spark SQL

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Phoenix  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLA scale-out RDBMS with evolutionary schema built on Apache HBaseSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSSpatial DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score21.72
Rank#29  Overall
#1  Spatial DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebitnine.net/­agensgraphphoenix.apache.orgpostgis.netspark.apache.org/­sql
Technical documentationbitnine.net/­documentationphoenix.apache.orgpostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBitnine Global Inc.Apache Software FoundationApache Software Foundation
Initial release2016201420052014
Current release2.1, December 20185.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4.2, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2.0Open Source infoGPL v2.0Open Source infoApache 2.0
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.
Implementation languageCJavaCScala
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows
Linux
OS X
Windows
Data schemedepending on used data modelyes infolate-bound, schema-on-read capabilitiesyesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyesyesSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
JDBCJDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsuser defined functionsno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingyes infobased on PostgreSQLyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
yes infobased on PostgreSQLnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes infobased on PostgreSQLno

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More resources
AgensGraphApache PhoenixPostGISSpark SQL
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