DBMS > PouchDB vs. SiriDB vs. Spark SQL vs. STSdb vs. ToroDB

System Properties Comparison PouchDB vs. SiriDB vs. Spark SQL vs. STSdb vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

JavaScript DBMS with an API inspired by CouchDB

Open Source Time Series DBMS

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

pouchdb.com

siridb.com

spark.apache.org/sql

github.com/STSSoft/STSdb4

github.com/torodb/server

Technical documentation

pouchdb.com/guides

docs.siridb.com

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

Developer

Apache Software Foundation

Cesbit

Apache Software Foundation

STS Soft SC

8Kdata

Initial release

2012

2017

2014

2011

2016

Current release

7.1.1, June 2019

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

JavaScript

Scala

Java

Server operating systems

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

Linux

Linux
OS X
Windows

Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

yes

primitive types and user defined types (classes)

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

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

JDBC
ODBC

.NET Client API

Supported programming languages

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Java
Python
R
Scala

C#
Java

Server-side scripts

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

Sharding

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

User concepts

Access control

simple rights management via user accounts

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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