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DBMS > Datomic vs. EDB Postgres vs. Google Cloud Datastore vs. InterSystems Caché

System Properties Comparison Datomic vs. EDB Postgres vs. Google Cloud Datastore vs. InterSystems Caché

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems Caché  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 durabilityThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA multi-model DBMS and application server
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitewww.datomic.comwww.enterprisedb.comcloud.google.com/­datastorewww.intersystems.com/­products/­cache
Technical documentationdocs.datomic.comwww.enterprisedb.com/­docscloud.google.com/­datastore/­docsdocs.intersystems.com
DeveloperCognitectEnterpriseDBGoogleInterSystems
Initial release2012200520081997
Current release1.0.6735, June 202314, December 20212018.1.4, May 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoBSD for PostgreSQL-componentscommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
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 VMLinux
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freedepending on used data model
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.noyes infospecific XML-type available, but no XML query functionality.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engineyes
TriggersBy using transaction functionsyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peershorizontal partitioning infoby hash, list or rangeShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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 developmentnonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles

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More resources
DatomicEDB PostgresGoogle Cloud DatastoreInterSystems Caché
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