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DBMS > Datomic vs. Google Cloud Datastore vs. GridDB vs. Realm

System Properties Comparison Datomic vs. Google Cloud Datastore vs. GridDB vs. Realm

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridDB  Xexclude from comparisonRealm  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 PlatformScalable in-memory time series database optimized for IoT and Big DataA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSDocument storeTime Series DBMSDocument store
Secondary database modelsKey-value store
Relational 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websitewww.datomic.comcloud.google.com/­datastoregriddb.netrealm.io
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.griddb.netrealm.io/­docs
DeveloperCognitectGoogleToshiba CorporationRealm, acquired by MongoDB in May 2019
Initial release2012200820132014
Current release1.0.6735, June 20235.1, August 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source
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++
Server operating systemsAll OS with a Java VMhostedLinuxAndroid
Backend: server-less
iOS
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infonumerical, string, blob, geometry, boolean, timestampyes
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)SQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Enginenono inforuns within the applications so server-side scripts are unnecessary
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyesyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
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 within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID at container levelACID
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 developmentnoyesyes infoIn-Memory realm
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseyes
More information provided by the system vendor
DatomicGoogle Cloud DatastoreGridDBRealm
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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DatomicGoogle Cloud DatastoreGridDBRealm
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