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DBMS > Dolt vs. Hive vs. IRONdb vs. Kinetica vs. NSDb

System Properties Comparison Dolt vs. Hive vs. IRONdb vs. Kinetica vs. NSDb

Editorial information provided by DB-Engines
NameDolt  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA MySQL compatible DBMS with Git-like versioning of data and schemadata warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully 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 DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitegithub.com/­dolthub/­dolt
www.dolthub.com
hive.apache.orgwww.circonus.com/solutions/time-series-database/www.kinetica.comnsdb.io
Technical documentationdocs.dolthub.comcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comnsdb.io/­Architecture
DeveloperDoltHub IncApache Software Foundation infoinitially developed by FacebookCirconus LLC.Kinetica
Initial release20182012201720122017
Current release3.1.3, April 2022V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC and C++C, C++Java, Scala
Server operating systemsLinux
macOS
Windows
All OS with a Java VMLinuxLinuxLinux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesyes: 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 indexesyesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsCLI Client
HTTP REST
JDBC
ODBC
Thrift
HTTP APIJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Scala
Server-side scripts infoStored proceduresyes infocurrently in alpha releaseyes infouser defined functions and integration of map-reduceyes, in Luauser defined functionsno
Triggersyesnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneShardingAutomatic, metric affinity per nodeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.selectable replication factorconfigurable replication factor, datacenter awareSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupAccess rights for users, groups and rolesnoAccess rights for users and roles on table level

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More resources
DoltHiveIRONdbKineticaNSDb
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