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DBMS > AllegroGraph vs. Datomic vs. Firebird vs. Google Cloud Datastore

System Properties Comparison AllegroGraph vs. Datomic vs. Firebird vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonDatomic  Xexclude from comparisonFirebird  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFirebird is an open source RDBMS forked from Borland's InterBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMSDocument store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#199  Overall
#34  Document stores
#18  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.08
Rank#132  Overall
#64  Relational DBMS
Score22.45
Rank#31  Overall
#19  Relational DBMS
Score4.87
Rank#78  Overall
#12  Document stores
Websiteallegrograph.comwww.datomic.comwww.firebirdsql.orgcloud.google.com/­datastore
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.datomic.comwww.firebirdsql.org/­en/­reference-manualscloud.google.com/­datastore/­docs
DeveloperFranz Inc.CognitectFirebird FoundationGoogle
Initial release200420122000 infoAs fork of Borland's InterBase2008
Current release8.0, December 20231.0.6735, June 20235.0.0, January 2024
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infolimited edition freeOpen Source infoInitial Developer's Public Licensecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC and C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
hosted
Data schemeyes infoRDF schemasyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
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 possiblenono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoyesSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
Java
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infoTransaction FunctionsPSQLusing Google App Engine
TriggersyesBy using transaction functionsyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeswith Federationnone infoBut extensive use of caching in the application peersnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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.
Foreign keys infoReferential integritynonoyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyes
Durability infoSupport for making data persistentyesyes 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.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoUsers with fine-grained authorization conceptAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
AllegroGraphDatomicFirebirdGoogle Cloud Datastore
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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