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DBMS > Datomic vs. Google Cloud Spanner vs. Kinetica vs. NSDb

System Properties Comparison Datomic vs. Google Cloud Spanner vs. Kinetica vs. NSDb

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial 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
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­spannerwww.kinetica.comnsdb.io
Technical documentationdocs.datomic.comcloud.google.com/­spanner/­docsdocs.kinetica.comnsdb.io/­Architecture
DeveloperCognitectGoogleKinetica
Initial release2012201720122017
Current release1.0.7180, July 20247.1, August 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen 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, C++Java, Scala
Server operating systemsAll OS with a Java VMhostedLinuxLinux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes: 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 indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesClojure
Java
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Java
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functionsno
TriggersBy using transaction functionsnoyes infotriggers when inserted values for one or more columns fall within a specified range
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 with 3 replicas for regional instances.Source-replica 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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnono
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)yesyesUsing 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 infoGPU vRAM or System RAM
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level

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More resources
DatomicGoogle Cloud SpannerKineticaNSDb
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