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DBMS > Fujitsu Enterprise Postgres vs. Hazelcast vs. Sphinx vs. Transbase

System Properties Comparison Fujitsu Enterprise Postgres vs. Hazelcast vs. Sphinx vs. Transbase

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonTransbase  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.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.postgresql.fastware.comhazelcast.comsphinxsearch.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationwww.postgresql.fastware.com/­product-manualshazelcast.org/­imdg/­docssphinxsearch.com/­docswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyHazelcastSphinx Technologies Inc.Transaction Software GmbH
Initial release200820011987
Current releaseFujitsu Enterprise Postgres 14, January 20225.3.6, November 20233.5.1, February 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC++C and C++
Server operating systemsLinux
Windows
All OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yes infothe object must implement a serialization strategyno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocolADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor Servicesnoyes
Triggersyesyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoyes
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlnofine grained access rights according to SQL-standard

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