DBMS > DataFS vs. NSDb vs. PouchDB vs. Spark SQL

System Properties Comparison DataFS vs. NSDb vs. PouchDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

JavaScript DBMS with an API inspired by CouchDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

Technical documentation

dev.mobiland.com/Overview.xsp

nsdb.io/Architecture

pouchdb.com/guides

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Mobiland AG

Apache Software Foundation

Initial release

2018

2017

2012

2014

Current release

1.1.263, October 2022

7.1.1, June 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java, Scala

JavaScript

Scala

Server operating systems

Windows

Linux
macOS

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

Linux
OS X
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

all fields are automatically indexed

yes

via views

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

gRPC
HTTP REST
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

Java
Scala

JavaScript

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

with a proxy-based framework, named couchdb-lounge

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

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

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 capabilities

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

yes

User concepts

Access control

Windows-Profile

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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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