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DBMS > HugeGraph vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx vs. Yanza

System Properties Comparison HugeGraph vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx vs. Yanza

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databasesTime Series DBMS for IoT Applications
Primary database modelGraph DBMSSearch engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engineTime Series DBMS
Secondary database modelsVector DBMS
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
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.comyanza.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperBaiduMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.Yanza
Initial release20182015199420012015
Current release0.9V118.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsLinux
macOS
Unix
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnonono
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 infoonly with the Berkeley DB XML editionno
Secondary indexesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)no
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocolHTTP API
Supported programming languagesGroovy
Java
Python
C#
Java
JavaScript
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
any language that supports HTTP calls
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnononono
Triggersnonoyes infoonly for the SQL APInoyes infoTimer and event based
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 servicenoneSharding infoPartitioning is done manually, search queries against distributed index is supportednone
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 replicationnonenone
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 graphnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationnonono

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More resources
HugeGraphMicrosoft Azure AI SearchOracle Berkeley DBSphinxYanza
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