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DBMS > Fujitsu Enterprise Postgres vs. GridDB vs. HugeGraph vs. Microsoft Azure AI Search

System Properties Comparison Fujitsu Enterprise Postgres vs. GridDB vs. HugeGraph vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonGridDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  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.Scalable in-memory time series database optimized for IoT and Big DataA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMSTime Series DBMSGraph DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitewww.postgresql.fastware.comgriddb.netgithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­search
Technical documentationwww.postgresql.fastware.com/­product-manualsdocs.griddb.nethugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­search
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyToshiba CorporationBaiduMicrosoft
Initial release201320182015
Current releaseFujitsu Enterprise Postgres 14, January 20225.1, August 20220.9V1
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Java
Server operating systemsLinux
Windows
LinuxLinux
macOS
Unix
hosted
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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 indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Groovy
Java
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functionsnoasynchronous Gremlin script jobsno
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseUsers, roles and permissionsyes infousing Azure authentication
More information provided by the system vendor
Fujitsu Enterprise PostgresGridDBHugeGraphMicrosoft Azure AI Search
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Fujitsu Enterprise PostgresGridDBHugeGraphMicrosoft Azure AI Search
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