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DBMS > Datomic vs. Google Cloud Datastore vs. Interbase vs. InterSystems Caché vs. Oracle Rdb

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Interbase vs. InterSystems Caché vs. Oracle Rdb

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterbase  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonOracle Rdb  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
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 PlatformLight-weight proven RDBMS infooriginally from BorlandA multi-model DBMS and application server
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
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
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score1.08
Rank#184  Overall
#85  Relational DBMS
Websitewww.datomic.comcloud.google.com/­datastorewww.embarcadero.com/­products/­interbasewww.intersystems.com/­products/­cachewww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.embarcadero.com/­products/­interbasedocs.intersystems.comwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperCognitectGoogleEmbarcaderoInterSystemsOracle, originally developed by Digital Equipment Corporation (DEC)
Initial release20122008198419971984
Current release1.0.6735, June 2023InterBase 2020, December 20192018.1.4, May 20207.4.1.1, 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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 VMhostedAndroid
iOS
Linux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
HP Open VMS
Data schemeyesschema-freeyesdepending on used data modelFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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 infoexport as XML data possibleyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyesyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineyes infoInterbase procedure and trigger languageyes
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosInterbase Change ViewsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDyes, on a single node
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentnoyesyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users, groups and roles

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More resources
DatomicGoogle Cloud DatastoreInterbaseInterSystems CachéOracle Rdb
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