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DBMS > Faircom DB vs. Fujitsu Enterprise Postgres vs. JaguarDB vs. Spark SQL

System Properties Comparison Faircom DB vs. Fujitsu Enterprise Postgres vs. JaguarDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonJaguarDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Performant, highly scalable DBMS for AI and IoT applicationsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value store
Relational DBMS
Relational DBMSKey-value store
Vector DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.postgresql.fastware.comwww.jaguardb.comspark.apache.org/­sql
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.postgresql.fastware.com/­product-manualswww.jaguardb.com/­support.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFairCom CorporationPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyDataJaguar, Inc.Apache Software Foundation
Initial release197920152014
Current releaseV12, November 2020Fujitsu Enterprise Postgres 14, January 20223.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen 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 languageANSI C, C++CC++ infothe server part. Clients available in other languagesScala
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesyesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statements
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningpartitioning by range, list and by hashShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardrights management via user accountsno
More information provided by the system vendor
Faircom DB infoformerly c-treeACEFujitsu Enterprise PostgresJaguarDBSpark SQL
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Faircom DB infoformerly c-treeACEFujitsu Enterprise PostgresJaguarDBSpark SQL
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