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DBMS > AllegroGraph vs. Badger vs. Datomic vs. Google Cloud Datastore vs. IBM Db2 warehouse

System Properties Comparison AllegroGraph vs. Badger vs. Datomic vs. Google Cloud Datastore vs. IBM Db2 warehouse

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBadger  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  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 durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud-based data warehousing service
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.37
Rank#160  Overall
#74  Relational DBMS
Websiteallegrograph.comgithub.com/­dgraph-io/­badgerwww.datomic.comcloud.google.com/­datastorewww.ibm.com/­products/­db2/­warehouse
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperFranz Inc.DGraph LabsCognitectGoogleIBM
Initial release20042017201220082014
Current release8.0, December 20231.0.7075, December 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, Clojure
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedhosted
Data schemeyes infoRDF schemasschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes, details hereyes
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 possiblenononono infoImport/export of XML data possible
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenonoSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
GoClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyes infoTransaction Functionsusing Google App EnginePL/SQL, SQL PL
TriggersyesnoBy using transaction functionsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeswith Federationnonenone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone infoBut extensive use of caching in the application peersMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphBadgerDatomicGoogle Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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