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DBMS > Apache IoTDB vs. Blazegraph vs. FatDB vs. GridDB

System Properties Comparison Apache IoTDB vs. Blazegraph vs. FatDB vs. GridDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonFatDB  Xexclude from comparisonGridDB  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelTime Series DBMSGraph DBMS
RDF store
Document store
Key-value store
Time Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websiteiotdb.apache.orgblazegraph.comgriddb.net
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwiki.blazegraph.comdocs.griddb.net
DeveloperApache Software FoundationBlazegraphFatCloudToshiba Corporation
Initial release2018200620122013
Current release1.1.0, April 20232.1.5, March 20195.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoextended commercial license availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC#C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
WindowsLinux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSPARQL is used as query languageno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyesyes infovia applicationsno
Triggersyesnoyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyes infoRelationships in Graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID at container level
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.yesyes
User concepts infoAccess controlyesSecurity and Authentication via Web Application Container (Tomcat, Jetty)no infoCan implement custom security layer via applicationsAccess rights for users can be defined per database
More information provided by the system vendor
Apache IoTDBBlazegraphFatDBGridDB
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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Apache IoTDBBlazegraphFatDBGridDB
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