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DBMS > Fujitsu Enterprise Postgres vs. HBase vs. Kinetica vs. Sphinx

System Properties Comparison Fujitsu Enterprise Postgres vs. HBase vs. Kinetica vs. Sphinx

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Wide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.postgresql.fastware.comhbase.apache.orgwww.kinetica.comsphinxsearch.com
Technical documentationwww.postgresql.fastware.com/­product-manualshbase.apache.org/­book.htmldocs.kinetica.comsphinxsearch.com/­docs
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software Foundation infoApache top-level project, originally developed by PowersetKineticaSphinx Technologies Inc.
Initial release200820122001
Current releaseFujitsu Enterprise Postgres 14, January 20222.3.4, January 20217.1, August 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC, C++C++
Server operating systemsLinux
Windows
Linux
Unix
Windows infousing Cygwin
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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.nono
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyes infoCoprocessors in Javauser defined functionsno
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table levelno
More information provided by the system vendor
Fujitsu Enterprise PostgresHBaseKineticaSphinx
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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Fujitsu Enterprise PostgresHBaseKineticaSphinx
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