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DBMS > Blazegraph vs. GridDB vs. SiteWhere vs. Spark SQL vs. Sphinx

System Properties Comparison Blazegraph vs. GridDB vs. SiteWhere vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGridDB  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  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.Scalable in-memory time series database optimized for IoT and Big DataM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Time Series DBMSTime Series DBMSRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteblazegraph.comgriddb.netgithub.com/­sitewhere/­sitewherespark.apache.org/­sqlsphinxsearch.com
Technical documentationwiki.blazegraph.comdocs.griddb.netsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperBlazegraphToshiba CorporationSiteWhereApache Software FoundationSphinx Technologies Inc.
Initial release20062013201020142001
Current release2.1.5, March 20195.1, August 20223.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++JavaScalaC++
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyespredefined schemeyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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 indexesyesyesnonoyes infofull-text index on all search fields
SQL infoSupport of SQLSPARQL is used as query languageSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnonono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on HBaseyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor infobased on HBasenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnonono
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.yesnono
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users can be defined per databaseUsers with fine-grained authorization conceptnono
More information provided by the system vendor
BlazegraphGridDBSiteWhereSpark SQLSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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