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DBMS > AllegroGraph vs. Firebase Realtime Database vs. Google Cloud Datastore vs. ToroDB vs. Yaacomo

System Properties Comparison AllegroGraph vs. Firebase Realtime Database vs. Google Cloud Datastore vs. ToroDB vs. Yaacomo

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonToroDB  Xexclude from comparisonYaacomo  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA MongoDB-compatible JSON document store, built on top of PostgreSQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeDocument 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
Score14.29
Rank#39  Overall
#6  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Websiteallegrograph.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastoregithub.com/­torodb/­serveryaacomo.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docs
DeveloperFranz Inc.Google infoacquired by Google 2014Google8KdataQ2WEB GmbH
Initial release20042012200820162009
Current release8.0, December 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialOpen Source infoAGPL-V3commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsLinux
OS X
Windows
hostedhostedAll OS with a Java 7 VMAndroid
Linux
Windows
Data schemeyes infoRDF schemasschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infostring, integer, double, boolean, date, object_idyes
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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lisplimited functionality with using 'rules'using Google App Engine
TriggersyesCallbacks are triggered when data changesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replicationSource-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 configurationEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate 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.Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphFirebase Realtime DatabaseGoogle Cloud DatastoreToroDBYaacomo
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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More resources
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