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DBMS > AllegroGraph vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Hazelcast

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

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparison
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 widely adopted in-memory data grid
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeDocument storeKey-value store
Secondary database modelsSpatial DBMSDocument store infoJSON support with IMDG 3.12
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
Score13.64
Rank#39  Overall
#6  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Websiteallegrograph.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorehazelcast.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docshazelcast.org/­imdg/­docs
DeveloperFranz Inc.Google infoacquired by Google 2014GoogleHazelcast
Initial release2004201220082008
Current release8.0, December 20235.3.6, November 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
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 VM
Data schemeyes infoRDF schemasschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, 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 possiblenonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query language (GQL)SQL-like query language
APIs and other access methodsRESTful HTTP API
SPARQL
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lisplimited functionality with using 'rules'using Google App Engineyes infoEvent Listeners, Executor Services
TriggersyesCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes
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.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commited
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 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)Role-based access control
More information provided by the system vendor
AllegroGraphFirebase Realtime DatabaseGoogle Cloud DatastoreHazelcast
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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