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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonPrometheus  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 PlatformA multi-model DBMS and application serverOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSDocument storeKey-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­datastorewww.intersystems.com/­products/­cacheprometheus.io
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.intersystems.comprometheus.io/­docs
DeveloperCognitectGoogleInterSystems
Initial release2012200819972015
Current release1.0.6735, June 20232018.1.4, May 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache 2.0
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, ClojureGo
Server operating systemsAll OS with a Java VMhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Windows
Data schemeyesschema-freedepending on used data modelyes
Typing infopredefined data types such as float or dateyesyes, details hereyesNumeric data only
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.nonoyesno infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)yesno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineyesno
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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 Consistencynone
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 TransactionsACIDno
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 developmentnoyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesno

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More resources
DatomicGoogle Cloud DatastoreInterSystems CachéPrometheus
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