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

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

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSFully vectorized database across both GPUs and CPUsSearch-as-a-service for web and mobile app developmentOpen 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 DBMSRelational DBMSSearch engineSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.comwww.teradata.com
Technical documentationhugegraph.apache.org/­docsdocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docsdocs.teradata.com
DeveloperBaiduKineticaMicrosoftSphinx Technologies Inc.Teradata
Initial release20182012201520011984
Current release0.97.1, August 2021V13.5.1, 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 servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++
Server operating systemsLinux
macOS
Unix
LinuxhostedFreeBSD
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.nononoyes
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 SQLnoSQL-like DML and DDL statementsnoSQL-like query language (SphinxQL)yes infoSQL 2016 + extensions
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIProprietary protocol.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGroovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
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 jobsuser defined functionsnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoImplicit feature of the cloud serviceSharding 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 HBaseSource-replica replicationyes infoImplicit feature of the cloud servicenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
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.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlUsers, roles and permissionsAccess rights for users and roles on table levelyes infousing Azure authenticationnofine grained access rights according to SQL-standard

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More resources
HugeGraphKineticaMicrosoft Azure AI SearchSphinxTeradata
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