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DBMS > Datomic vs. Google Cloud Datastore

System Properties Comparison Datomic vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  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 Platform
Primary database modelRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.08
Rank#132  Overall
#64  Relational DBMS
Score4.87
Rank#78  Overall
#12  Document stores
Websitewww.datomic.comcloud.google.com/­datastore
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperCognitectGoogle
Initial release20122008
Current release1.0.6735, June 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, Clojure
Server operating systemsAll OS with a Java VMhosted
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details here
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
Secondary indexesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engine
TriggersBy using transaction functionsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflow
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.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
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 developmentno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatomicGoogle Cloud Datastore
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