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

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

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentWidely 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 databasesA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelGraph DBMSSearch engineRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engineDocument store
Graph DBMS
Secondary database modelsVector 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
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchwww.postgresql.orgsphinxsearch.comsurrealdb.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchwww.postgresql.org/­docssphinxsearch.com/­docssurrealdb.com/­docs
DeveloperBaiduMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.SurrealDB Ltd
Initial release201820151989 info1989: Postgres, 1996: PostgreSQL20012022
Current release0.9V116.3, May 20243.5.1, February 2023v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSDOpen Source infoGPL version 2, commercial licence availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++Rust
Server operating systemsLinux
macOS
Unix
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyes infostandard with numerous extensionsSQL-like query language (SphinxQL)SQL-like query language
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolGraphQL
RESTful HTTP API
WebSocket
Supported programming languagesGroovy
Java
Python
C#
Java
JavaScript
Python
.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
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnonoyesno
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 servicepartitioning 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 serviceSource-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 Consistency
Foreign keys infoReferential integrityyes infoedges in graphnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesnono
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationfine grained access rights according to SQL-standardnoyes, based on authentication and database rules

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More resources
HugeGraphMicrosoft Azure AI SearchPostgreSQLSphinxSurrealDB
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