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DBMS > Blazegraph vs. Google Cloud Bigtable vs. GridDB vs. SiriDB

System Properties Comparison Blazegraph vs. Google Cloud Bigtable vs. GridDB vs. SiriDB

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonSiriDB  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataOpen Source Time Series DBMS
Primary database modelGraph DBMS
RDF store
Key-value store
Wide column store
Time Series DBMSTime Series DBMS
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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteblazegraph.comcloud.google.com/­bigtablegriddb.netsiridb.com
Technical documentationwiki.blazegraph.comcloud.google.com/­bigtable/­docsdocs.griddb.netdocs.siridb.com
DeveloperBlazegraphGoogleToshiba CorporationCesbit
Initial release2006201520132017
Current release2.1.5, March 20195.1, August 2022
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemsLinux
OS X
Windows
hostedLinuxLinux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesnoyes infonumerical, string, blob, geometry, boolean, timestampyes infoNumeric data
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 indexesyesnoyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesnonono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyes infoRelationships in Graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID at container levelno
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.noyesyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databasesimple rights management via user accounts
More information provided by the system vendor
BlazegraphGoogle Cloud BigtableGridDBSiriDB
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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More resources
BlazegraphGoogle Cloud BigtableGridDBSiriDB
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