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DBMS > Apache Phoenix vs. Faircom EDGE vs. Greenplum vs. InfinityDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Faircom EDGE vs. Greenplum vs. InfinityDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGreenplum  Xexclude from comparisonInfinityDB  Xexclude from comparisonSpark SQL  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 environmentsAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A Java embedded Key-Value Store which extends the Java Map interfaceSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.faircom.com/­products/­faircom-edgegreenplum.orgboilerbay.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.greenplum.orgboilerbay.com/­infinitydb/­manualspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFairCom CorporationPivotal Software Inc.Boiler Bay Inc.Apache Software Foundation
Initial release20141979200520022014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V3, October 20207.0.0, September 20234.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
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++JavaScala
Server operating systemsLinux
Unix
Windows
Android
Linux infoARM, x86
Raspbian
Windows
LinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.noyesyes infosince Version 4.2nono
Secondary indexesyesyesyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLyesyes infoANSI SQL queriesyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
Java
Perl
Python
R
JavaJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yesnono
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingnoneyes, utilizing Spark Core
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 replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynoyes infowhen using SQLyesno infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonono
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.fine grained access rights according to SQL-standardnono

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More resources
Apache PhoenixFaircom EDGE infoformerly c-treeEDGEGreenplumInfinityDBSpark SQL
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