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DBMS > Datomic vs. Google Cloud Datastore vs. Kinetica vs. RethinkDB

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Kinetica vs. RethinkDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Websitewww.datomic.comcloud.google.com/­datastorewww.kinetica.comrethinkdb.com
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.kinetica.comrethinkdb.com/­docs
DeveloperCognitectGoogleKineticaThe Linux Foundation infosince July 2017
Initial release2012200820122009
Current release1.0.6735, June 20237.1, August 20212.4.1, August 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC, C++C++
Server operating systemsAll OS with a Java VMhostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infostring, binary, float, bool, date, geometry
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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
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
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineuser defined functions
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeClient-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC based
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 infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyes infousers and table-level permissions

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More resources
DatomicGoogle Cloud DatastoreKineticaRethinkDB
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