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DBMS > HugeGraph vs. Microsoft Azure AI Search vs. RavenDB vs. Sphinx vs. Yanza

System Properties Comparison HugeGraph vs. Microsoft Azure AI Search vs. RavenDB vs. Sphinx vs. Yanza

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonRavenDB  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 developmentOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen source search engine for searching in data from different sources, e.g. relational databasesTime Series DBMS for IoT Applications
Primary database modelGraph DBMSSearch engineDocument storeSearch engineTime Series DBMS
Secondary database modelsVector DBMSGraph 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
Score2.92
Rank#101  Overall
#18  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchravendb.netsphinxsearch.comyanza.com
Technical documentationhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchravendb.net/­docssphinxsearch.com/­docs
DeveloperBaiduMicrosoftHibernating RhinosSphinx Technologies Inc.Yanza
Initial release20182015201020012015
Current release0.9V15.4, July 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3, commercial 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#C++
Server operating systemsLinux
macOS
Unix
hostedLinux
macOS
Raspberry Pi
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.nonono
Secondary indexesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnonoSQL-like query language (RQL)SQL-like query language (SphinxQL)no
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocolHTTP API
Supported programming languagesGroovy
Java
Python
C#
Java
JavaScript
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 jobsnoyesnono
Triggersnonoyesnoyes 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 serviceShardingSharding 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 serviceMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availablenono
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.yesno
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationAuthorization levels configured per client per databasenono

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More resources
HugeGraphMicrosoft Azure AI SearchRavenDBSphinxYanza
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