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DBMS > Datomic vs. Firebase Realtime Database vs. Google Cloud Datastore vs. RDFox

System Properties Comparison Datomic vs. Firebase Realtime Database vs. Google Cloud Datastore vs. RDFox

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud-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 PlatformHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSDocument storeDocument storeGraph DBMS
RDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitewww.datomic.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastorewww.oxfordsemantic.tech
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docsdocs.oxfordsemantic.tech
DeveloperCognitectGoogle infoacquired by Google 2014GoogleOxford Semantic Technologies
Initial release2012201220082017
Current release1.0.7075, December 20236.0, Septermber 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercial
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, ClojureC++
Server operating systemsAll OS with a Java VMhostedhostedLinux
macOS
Windows
Data schemeyesschema-freeschema-freeyes infoRDF schemas
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP APIAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
SPARQL 1.1
Supported programming languagesClojure
Java
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionslimited functionality with using 'rules'using Google App Engine
TriggersBy using transaction functionsCallbacks are triggered when data changesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Roles, resources, and access types

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More resources
DatomicFirebase Realtime DatabaseGoogle Cloud DatastoreRDFox
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