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DBMS > Datomic vs. EsgynDB vs. Google Cloud Datastore vs. Warp 10

System Properties Comparison Datomic vs. EsgynDB vs. Google Cloud Datastore vs. Warp 10

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.datomic.comwww.esgyn.cncloud.google.com/­datastorewww.warp10.io
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docswww.warp10.io/­content/­02_Getting_started
DeveloperCognitectEsgynGoogleSenX
Initial release2012201520082015
Current release1.0.6735, June 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoApache License 2.0
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++, JavaJava
Server operating systemsAll OS with a Java VMLinuxhostedLinux
OS X
Windows
Data schemeyesyesschema-freeschema-free
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Jupyter
WebSocket
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava Stored Proceduresusing Google App Engineyes infoWarpScript
TriggersBy using transaction functionsnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication between multi datacentersMulti-source replication using Paxosselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes 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 infobased on HBase
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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 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)Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
DatomicEsgynDBGoogle Cloud DatastoreWarp 10
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