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DBMS > Datomic vs. GigaSpaces vs. Google Cloud Datastore vs. InterSystems Caché

System Properties Comparison Datomic vs. GigaSpaces vs. Google Cloud Datastore vs. InterSystems Caché

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGigaSpaces  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 durabilityHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA multi-model DBMS and application server
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Document storeKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitewww.datomic.comwww.gigaspaces.comcloud.google.com/­datastorewww.intersystems.com/­products/­cache
Technical documentationdocs.datomic.comdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­datastore/­docsdocs.intersystems.com
DeveloperCognitectGigaspaces TechnologiesGoogleInterSystems
Initial release2012200020081997
Current release1.0.6735, June 202315.5, September 20202018.1.4, May 2020
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial
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, ClojureJava, C++, .Net
Server operating systemsAll OS with a Java VMLinux
macOS
Solaris
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-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.nono infoXML can be used for describing objects metadatanoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP APIGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesusing Google App Engineyes
TriggersBy using transaction functionsyes, event driven architectureCallbacks using the Google Apps Engineyes
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 infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate 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 integritynonoyes 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 datayesyesyesyes
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 developmentyesnoyes
User concepts infoAccess controlnoRole-based access controlAccess 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
DatomicGigaSpacesGoogle Cloud DatastoreInterSystems Caché
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