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DBMS > AllegroGraph vs. Badger vs. Datomic vs. GridDB

System Properties Comparison AllegroGraph vs. Badger vs. Datomic vs. GridDB

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBadger  Xexclude from comparisonDatomic  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big Data
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.16
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.20
Rank#325  Overall
#49  Key-value stores
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Websiteallegrograph.comgithub.com/­dgraph-io/­badgerwww.datomic.comgriddb.net
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comdocs.griddb.net
DeveloperFranz Inc.DGraph LabsCognitectToshiba Corporation
Initial release2004201720122013
Current release8.0, December 20231.0.6735, June 20235.1, August 2022
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercial infolimited edition freeOpen 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 languageGoJava, ClojureC++
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
Data schemeyes infoRDF schemasschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes 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.no infobulk load of XML files possiblenonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSPARQL is used as query languagenonoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
GoClojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyes infoTransaction Functionsno
TriggersyesnoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodeswith Federationnonenone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone infoBut extensive use of caching in the application peersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and developmentyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnonoAccess rights for users can be defined per database
More information provided by the system vendor
AllegroGraphBadgerDatomicGridDB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
1. 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
News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AllegroGraphBadgerDatomicGridDB
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