DB-EnginesextremeDB - Data management wherever you need itEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Datomic vs. Kinetica vs. NSDb vs. Vitess

System Properties Comparison Datomic vs. Kinetica vs. NSDb vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websitewww.datomic.comwww.kinetica.comnsdb.iovitess.io
Technical documentationdocs.datomic.comdocs.kinetica.comnsdb.io/­Architecturevitess.io/­docs
DeveloperCognitectKineticaThe Linux Foundation, PlanetScale
Initial release2012201220172013
Current release1.0.7180, July 20247.1, August 202115.0.2, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC, C++Java, ScalaGo
Server operating systemsAll OS with a Java VMLinuxLinux
macOS
Docker
Linux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.nonono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesClojure
Java
C++
Java
JavaScript (Node.js)
Python
Java
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsnoyes infoproprietary syntax
TriggersBy using transaction functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
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 peersSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesUsing Apache Luceneyes
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 developmentyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlnoAccess rights for users and roles on table levelUsers with fine-grained authorization concept infono user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
DatomicKineticaNSDbVitess
Recent citations in the news

Brazil’s Nubank Acquires US Software Firm Cognitect
30 July 2020, Nearshore Americas

Lucas Cavalcanti on Using Clojure, Microservices, Hexagonal Architecture and Public Cloud at Nubank
16 August 2021, InfoQ.com

Brazil’s Nubank acquires US software firm Cognitect, creator of Clojure and Datomic
24 July 2020, LatamList

Nubank acquires US company; PayPal studies cryptocurrencies
24 July 2020, iupana.com

Zoona Case Study
16 December 2017, AWS Blog

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks & Files

provided by Google News

Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era
20 May 2024, InfoQ.com

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

CNCF’s Vitess Scales MySQL with the Help of Kubernetes
9 February 2018, The New Stack

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here