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DBMS > AllegroGraph vs. Badger vs. Google Cloud Datastore vs. TimesTen

System Properties Comparison AllegroGraph vs. Badger vs. Google Cloud Datastore vs. TimesTen

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTimesTen  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteallegrograph.comgithub.com/­dgraph-io/­badgercloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperFranz Inc.DGraph LabsGoogleOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2004201720081998
Current release8.0, December 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGo
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Solaris
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyes infoRDF schemasschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes, 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 possiblenonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Go.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnousing Google App EnginePL/SQL
TriggersyesnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate 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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoAccess 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
AllegroGraphBadgerGoogle Cloud DatastoreTimesTen
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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