DBMS > Kinetica vs. NSDb vs. Tkrzw vs. UniData,UniVerse

System Properties Comparison Kinetica vs. NSDb vs. Tkrzw vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

www.kinetica.com

nsdb.io

dbmx.net/tkrzw

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.kinetica.com

nsdb.io/Architecture

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Kinetica

Mikio Hirabayashi

Rocket Software

Initial release

2012

2017

2020

1985

Current release

7.1, August 2021

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java, Scala

C++

Server operating systems

Linux

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

optional

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Java
Scala

C++
Java
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

using specific database classes

User concepts

Access control

Access rights for users and roles on table level

Access rights according to SQL-standard and operating system based

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More resources

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