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DBMS > Apache Phoenix vs. Faircom EDGE vs. Kinetica vs. PostgreSQL

System Properties Comparison Apache Phoenix vs. Faircom EDGE vs. Kinetica vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonKinetica  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully vectorized database across both GPUs and CPUsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitephoenix.apache.orgwww.faircom.com/­products/­faircom-edgewww.kinetica.comwww.postgresql.org
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.kinetica.comwww.postgresql.org/­docs
DeveloperApache Software FoundationFairCom CorporationKineticaPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2014197920121989 info1989: Postgres, 1996: PostgreSQL
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V3, October 20207.1, August 202116.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C, C++C
Server operating systemsLinux
Unix
Windows
Android
Linux infoARM, x86
Raspbian
Windows
LinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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.noyesnoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyes infoANSI SQL queriesSQL-like DML and DDL statementsyes infostandard with numerous extensions
APIs and other access methodsJDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++user defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
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 Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.yesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
Apache PhoenixFaircom EDGE infoformerly c-treeEDGEKineticaPostgreSQL
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