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DBMS > HugeGraph vs. Microsoft Azure AI Search vs. Netezza vs. Sphinx vs. Teradata

System Properties Comparison HugeGraph vs. Microsoft Azure AI Search vs. Netezza vs. Sphinx vs. Teradata

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentData warehouse and analytics appliance part of IBM PureSystemsOpen source search engine for searching in data from different sources, e.g. relational databasesA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelGraph DBMSSearch engineRelational DBMSSearch engineRelational DBMS
Secondary database modelsVector DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchwww.ibm.com/­products/­netezzasphinxsearch.comwww.teradata.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docsdocs.teradata.com
DeveloperBaiduMicrosoftIBMSphinx Technologies Inc.Teradata
Initial release20182015200020011984
Current release0.9V13.5.1, February 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
macOS
Unix
hostedLinux infoincluded in applianceFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
hosted
Linux
Data schemeyesyesyesyesyes
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
Secondary indexesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fieldsyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoyesSQL-like query language (SphinxQL)yes infoSQL 2016 + extensions
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIJDBC
ODBC
OLE DB
Proprietary protocol.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGroovy
Java
Python
C#
Java
JavaScript
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnoyesnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonononoyes
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 serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoHashing
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 replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnononoyes
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.yesnoyes
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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More resources
HugeGraphMicrosoft Azure AI SearchNetezza infoAlso called PureData System for Analytics by IBMSphinxTeradata
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