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DBMS > AgensGraph vs. Apache Druid vs. FatDB vs. GridDB

System Properties Comparison AgensGraph vs. Apache Druid vs. FatDB vs. GridDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Druid  Xexclude from comparisonFatDB  Xexclude from comparisonGridDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA .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 modelGraph DBMS
Relational DBMS
Relational DBMS
Time Series DBMS
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
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Websitebitnine.net/­agensgraphdruid.apache.orggriddb.net
Technical documentationbitnine.net/­documentationdruid.apache.org/­docs/­latest/­designdocs.griddb.net
DeveloperBitnine Global Inc.Apache Software Foundation and contributorsFatCloudToshiba Corporation
Initial release2016201220122013
Current release2.1, December 201829.0.1, April 20245.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache license v2commercialOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC#C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
WindowsLinux
Data schemedepending on used data modelyes infoschema-less columns are supportedschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL for queryingno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsCypher Query Language
JDBC
JDBC
RESTful HTTP/JSON API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC
Java
JavaScript
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoyes infovia applicationsno
Triggersnonoyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID 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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno infoCan implement custom security layer via applicationsAccess rights for users can be defined per database
More information provided by the system vendor
AgensGraphApache DruidFatDBGridDB
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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AgensGraphApache DruidFatDBGridDB
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