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DBMS > Blazegraph vs. Databricks vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Blazegraph vs. Databricks vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonDatabricks  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Graph DBMSSearch engineSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteblazegraph.comwww.databricks.comgithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationwiki.blazegraph.comdocs.databricks.comhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperBlazegraphDatabricksBaiduMicrosoftSphinx Technologies Inc.
Initial release20062013201820152001
Current release2.1.5, March 20190.9V13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinux
OS X
Windows
hostedLinux
macOS
Unix
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyesno
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.yesnono
Secondary indexesyesyesyes infoalso supports composite index and range indexyesyes infofull-text index on all search fields
SQL infoSupport of SQLSPARQL is used as query languagewith Databricks SQLnonoSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocol
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Python
R
Scala
Groovy
Java
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesasynchronous Gremlin script jobsnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesno
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Users, roles and permissionsyes infousing Azure authenticationno
More information provided by the system vendor
BlazegraphDatabricksHugeGraphMicrosoft Azure AI SearchSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BlazegraphDatabricksHugeGraphMicrosoft Azure AI SearchSphinx
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