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DBMS > Apache Phoenix vs. Faircom EDGE vs. Kinetica vs. Spark SQL vs. VoltDB

System Properties Comparison Apache Phoenix vs. Faircom EDGE vs. Kinetica vs. Spark SQL vs. VoltDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  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 CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websitephoenix.apache.orgwww.faircom.com/­products/­faircom-edgewww.kinetica.comspark.apache.org/­sqlwww.voltdb.com
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperApache Software FoundationFairCom CorporationKineticaApache Software FoundationVoltDB Inc.
Initial release20141979201220142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V3, October 20207.1, August 20213.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C, C++ScalaJava, C++
Server operating systemsLinux
Unix
Windows
Android
Linux infoARM, x86
Raspbian
Windows
LinuxLinux
OS X
Windows
Linux
OS X infofor development
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyesyes
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.noyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesyes infoANSI SQL queriesSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infoonly a subset of SQL 99
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
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
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
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++user defined functionsnoJava
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark CoreSharding
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 replicationnoneMulti-source replication
Source-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 Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infowhen using SQLyesnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyesyes infoSnapshots and command logging
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 levelnoUsers and roles with access to stored procedures

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More resources
Apache PhoenixFaircom EDGE infoformerly c-treeEDGEKineticaSpark SQLVoltDB
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