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DBMS > Datomic vs. Google Cloud Firestore vs. RethinkDB vs. Stardog

System Properties Comparison Datomic vs. Google Cloud Firestore vs. RethinkDB vs. Stardog

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonRethinkDB  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.DBMS for the Web with a mechanism to push updated query results to applications in realtime.Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSDocument storeDocument storeGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score6.63
Rank#54  Overall
#9  Document stores
Score2.58
Rank#105  Overall
#20  Document stores
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Websitewww.datomic.comfirebase.google.com/­products/­firestorerethinkdb.comwww.stardog.com
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­firestorerethinkdb.com/­docsdocs.stardog.com
DeveloperCognitectGoogleThe Linux Foundation infosince July 2017Stardog-Union
Initial release2012201720092010
Current release1.0.7180, July 20242.4.1, August 20207.3.0, May 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesschema-freeschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes infostring, binary, float, bool, date, geometryyes
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.nononono infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnononoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsRESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesClojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes, Firebase Rules & Cloud Functionsuser defined functions and aggregates, HTTP Server extensions in Java
TriggersBy using transaction functionsyes, with Cloud FunctionsClient-side triggers through changefeedsyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding inforange basednone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesAtomic single-document operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes
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 controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.yes infousers and table-level permissionsAccess rights for users and roles

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More resources
DatomicGoogle Cloud FirestoreRethinkDBStardog
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