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DBMS > Datomic vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. NSDb

System Properties Comparison Datomic vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. NSDb

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonNSDb  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 PlatformDistributed Event Store optimized for Internet of Things use casesScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMSDocument storeEvent Store
Time Series DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storensdb.io
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storensdb.io/­Architecture
DeveloperCognitectGoogleIBM
Initial release2012200820172017
Current release1.0.7180, July 20242.0
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial infofree developer edition availableOpen Source infoApache Version 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, ClojureC and C++Java, Scala
Server operating systemsAll OS with a Java VMhostedLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes: int, bigint, decimal, string
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 indexesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infothrough the embedded Spark runtimeSQL-like query language
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineyesno
TriggersBy using transaction functionsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosActive-active shard replication
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.Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageUsing Apache Lucene
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 developmentnoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
DatomicGoogle Cloud DatastoreIBM Db2 Event StoreNSDb
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