DBMS > Kinetica vs. Newts vs. OpenQM vs. PouchDB vs. STSdb

System Properties Comparison Kinetica vs. Newts vs. OpenQM vs. PouchDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Time Series DBMS based on Cassandra

QpenQM is a high-performance, self-tuning, multi-value DBMS

JavaScript DBMS with an API inspired by CouchDB

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

www.kinetica.com

opennms.github.io/newts

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

pouchdb.com

github.com/STSSoft/STSdb4

Technical documentation

docs.kinetica.com

github.com/OpenNMS/newts/wiki

pouchdb.com/guides

Developer

Kinetica

OpenNMS Group

Rocket Software, originally Martin Phillips

Apache Software Foundation

STS Soft SC

Initial release

2012

2014

1993

2012

2011

Current release

7.1, August 2021

3.4-12

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

GPLv2, commercial license available

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

JavaScript

Server operating systems

Linux

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Windows

Data scheme

yes

schema-free

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Java

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

View functions in JavaScript

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

User concepts

Access control

Access rights for users and roles on table level

Access rights can be defined down to the item level

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

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the 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 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

Kinetica Taps Dell for Hardware
12 June 2018, Finovate

provided by Google News

Getting Started with PouchDB Client-Side JavaScript Database
7 September 2016, SitePoint

Create Offline Web Apps Using Service Workers & PouchDB
7 March 2017, SitePoint

Building an Offline First App with PouchDB
10 March 2014, SitePoint

provided by Google News

Share this page