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DBMS > Apache Phoenix vs. Faircom DB vs. JaguarDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Faircom DB vs. JaguarDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonJaguarDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Performant, highly scalable DBMS for AI and IoT applicationsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value store
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.faircom.com/­products/­faircom-dbwww.jaguardb.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.jaguardb.com/­support.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFairCom CorporationDataJaguar, Inc.Apache Software Foundation
Initial release2014197920152014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V12, November 20203.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoGPL V3.0Open Source infoApache 2.0
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++ infothe server part. Clients available in other languagesScala
Server operating systemsLinux
Unix
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++nono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually Consistentnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyFine grained access rights according to SQL-standard with additional protections for filesrights management via user accountsno

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More resources
Apache PhoenixFaircom DB infoformerly c-treeACEJaguarDBSpark SQL
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