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DBMS > HugeGraph vs. Microsoft Azure AI Search vs. ObjectBox vs. PostgreSQL vs. Sphinx

System Properties Comparison HugeGraph vs. Microsoft Azure AI Search vs. ObjectBox vs. PostgreSQL vs. Sphinx

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonObjectBox  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentExtremely fast embedded database for small devices, IoT and MobileWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMSSearch engineObject oriented DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engine
Secondary database modelsVector DBMSTime Series DBMSDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchobjectbox.iowww.postgresql.orgsphinxsearch.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.objectbox.iowww.postgresql.org/­docssphinxsearch.com/­docs
DeveloperBaiduMicrosoftObjectBox LimitedPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.
Initial release2018201520171989 info1989: Postgres, 1996: PostgreSQL2001
Current release0.9V116.3, May 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache License 2.0Open Source infoBSDOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++CC++
Server operating systemsLinux
macOS
Unix
hostedAndroid
iOS
Linux
macOS
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyes infoalso supports composite index and range indexyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnononoyes infostandard with numerous extensionsSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary native APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languagesGroovy
Java
Python
C#
Java
JavaScript
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnonouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud servicenonepartitioning by range, list and (since PostgreSQL 11) by hashSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud serviceonline/offline synchronization between client and serverSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnonono
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationyesfine grained access rights according to SQL-standardno
More information provided by the system vendor
HugeGraphMicrosoft Azure AI SearchObjectBoxPostgreSQLSphinx
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