DBMS > EsgynDB vs. NSDb vs. PouchDB vs. SwayDB vs. ToroDB

System Properties Comparison EsgynDB vs. NSDb vs. PouchDB vs. SwayDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

JavaScript DBMS with an API inspired by CouchDB

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

github.com/torodb/server

Technical documentation

nsdb.io/Architecture

pouchdb.com/guides

Developer

Esgyn

Apache Software Foundation

Simer Plaha

8Kdata

Initial release

2015

2017

2012

2018

2016

Current release

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

Open Source

AGPL-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++, Java

Java, Scala

JavaScript

Scala

Java

Server operating systems

Linux

Linux
macOS

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

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

string, integer, double, boolean, date, object_id

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

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
Scala

JavaScript

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

Source-replica replication

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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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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