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DBMS > HugeGraph vs. Microsoft Azure AI Search vs. OceanBase vs. Pinecone vs. Sphinx

System Properties Comparison HugeGraph vs. Microsoft Azure AI Search vs. OceanBase vs. Pinecone vs. Sphinx

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOceanBase  Xexclude from comparisonPinecone  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentA distributed, high available RDBMS compatible with Oracle and MySQLA managed, cloud-native vector databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMSSearch engineRelational DBMSVector DBMSSearch engine
Secondary database modelsVector DBMSDocument store
Wide column store
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
Score1.66
Rank#147  Overall
#68  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchen.oceanbase.comwww.pinecone.iosphinxsearch.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchen.oceanbase.com/­docs/­oceanbase-databasedocs.pinecone.io/­docs/­overviewsphinxsearch.com/­docs
DeveloperBaiduMicrosoftOceanBase infopreviously Alibaba and Ant GroupPinecone Systems, IncSphinx Technologies Inc.
Initial release20182015201020192001
Current release0.9V14.3.0, April 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoCommercial license availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsLinux
macOS
Unix
hostedLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesString, Number, Booleanno
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.nonoyesno
Secondary indexesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesnoSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
RESTful HTTP APIProprietary protocol
Supported programming languagesGroovy
Java
Python
C#
Java
JavaScript
Python
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
PythonC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnoPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modeno
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 servicehorizontal partitioning (by hash, key, range, range columns, list, and list columns)Sharding 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 serviceMulti-source replication using Paxosnone
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 dataACIDnoACIDno
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.yesnono
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standardno

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More resources
HugeGraphMicrosoft Azure AI SearchOceanBasePineconeSphinx
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