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

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

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A 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 databases
Primary database modelRelational DBMSGraph DBMSSearch engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#185  Overall
#86  Relational DBMS
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
Websitewww.gbase.cngithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperGeneral Data Technology Co., Ltd.BaiduMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release20042018201519942001
Current releaseGBase 8a, GBase 8s, GBase 8c0.9V118.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, PythonJavaC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsLinuxLinux
macOS
Unix
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnono
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.yesnonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLStandard with numerous extensionsnonoyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
C API
JDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocol
Supported programming languagesC#Groovy
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
Server-side scripts infoStored proceduresuser defined functionsasynchronous Gremlin script jobsnonono
Triggersyesnonoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningyes 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 supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud serviceSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes
User concepts infoAccess controlyesUsers, roles and permissionsyes infousing Azure authenticationnono

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More resources
GBaseHugeGraphMicrosoft Azure AI SearchOracle Berkeley DBSphinx
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