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DBMS > Fujitsu Enterprise Postgres vs. HugeGraph vs. Sphinx vs. Vitess

System Properties Comparison Fujitsu Enterprise Postgres vs. HugeGraph vs. Sphinx vs. Vitess

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonHugeGraph  Xexclude from comparisonSphinx  Xexclude from comparisonVitess  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 fast-speed and highly-scalable Graph DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSGraph DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.postgresql.fastware.comgithub.com/­hugegraph
hugegraph.apache.org
sphinxsearch.comvitess.io
Technical documentationwww.postgresql.fastware.com/­product-manualshugegraph.apache.org/­docssphinxsearch.com/­docsvitess.io/­docs
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyBaiduSphinx Technologies Inc.The Linux Foundation, PlanetScale
Initial release201820012013
Current releaseFujitsu Enterprise Postgres 14, January 20220.93.5.1, February 202315.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++Go
Server operating systemsLinux
Windows
Linux
macOS
Unix
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeyesyesyesyes
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.no
Secondary indexesyesyes infoalso supports composite index and range indexyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesnoSQL-like query language (SphinxQL)yes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
TinkerPop Gremlin
Proprietary protocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Groovy
Java
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsasynchronous Gremlin script jobsnoyes infoproprietary syntax
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBasenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyes infoedges in graphnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes infotable locks or row locks depending on storage engine
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.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers, roles and permissionsnoUsers with fine-grained authorization concept infono user groups or roles

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Fujitsu Enterprise PostgresHugeGraphSphinxVitess
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