DBMS > Kinetica vs. NSDb vs. PouchDB vs. TerminusDB

System Properties Comparison Kinetica vs. NSDb vs. PouchDB vs. TerminusDB

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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

JavaScript DBMS with an API inspired by CouchDB

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
RDF store

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	2.18
Rank	#114	Overall
	#21	Document stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

Technical documentation

docs.kinetica.com

nsdb.io/Architecture

pouchdb.com/guides

terminusdb.github.io/terminusdb/#

Developer

Kinetica

Apache Software Foundation

DataChemist Ltd.

Initial release

2012

2017

2012

2018

Current release

7.1, August 2021

7.1.1, June 2019

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3

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

JavaScript

Prolog, Rust

Server operating systems

Linux

Linux
macOS

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

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

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

via views

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Java
Scala

JavaScript

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

yes

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

with a proxy-based framework, named couchdb-lounge

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Journaling Streams

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

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

Using Apache Lucene

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

in-memory journaling

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

Role-based access control

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More resources

DB-Engines blog posts

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

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