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DBMS > Blazegraph vs. GridDB vs. Kyligence Enterprise vs. Solr

System Properties Comparison Blazegraph vs. GridDB vs. Kyligence Enterprise vs. Solr

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGridDB  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonSolr  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 DataA distributed analytics engine for big data, built on top of Apache KylinA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Spatial 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
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteblazegraph.comgriddb.netkyligence.io/­kyligence-enterprisesolr.apache.org
Technical documentationwiki.blazegraph.comdocs.griddb.netsolr.apache.org/­resources.html
DeveloperBlazegraphToshiba CorporationKyligence, Inc.Apache Software Foundation
Initial release2006201320162006
Current release2.1.5, March 20195.1, August 20229.6.0, April 2024
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 availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaJava
Server operating systemsLinux
OS X
Windows
LinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infosupports customizable data types and automatic typing
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 indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSPARQL is used as query languageSQL92, SQL-like TQL (Toshiba Query Language)ANSI SQL for queries (using Apache Calcite)Solr Parallel SQL Interface
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoJava plugins
Triggersnoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container leveloptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users can be defined per databaseyes
More information provided by the system vendor
BlazegraphGridDBKyligence EnterpriseSolr
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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BlazegraphGridDBKyligence EnterpriseSolr
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