DBMS > Microsoft Azure Table Storage vs. OrigoDB vs. PouchDB vs. ReductStore vs. STSdb

System Properties Comparison Microsoft Azure Table Storage vs. OrigoDB vs. PouchDB vs. ReductStore vs. STSdb

Editorial information provided by DB-Engines

Name

Description

A Wide Column Store for rapid development using massive semi-structured datasets

A fully ACID in-memory object graph database

JavaScript DBMS with an API inspired by CouchDB

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Wide column store

Document store
Object oriented DBMS

Document store

Time Series DBMS

Key-value store

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

azure.microsoft.com/en-us/services/storage/tables

origodb.com

pouchdb.com

github.com/reductstore
www.reduct.store

github.com/STSSoft/STSdb4

Technical documentation

origodb.com/docs

pouchdb.com/guides

www.reduct.store/docs

Developer

Microsoft

Robert Friberg et al

Apache Software Foundation

ReductStore LLC

STS Soft SC

Initial release

2012

2009

under the name LiveDB

2012

2023

2011

Current release

7.1.1, June 2019

1.9, March 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++, Rust

Server operating systems

hosted

Linux
Windows

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

Docker
Linux
macOS
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

via views

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

.NET Client API

Supported programming languages

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net

JavaScript

C++
JavaScript (Node.js)
Python
Rust

C#
Java

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

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

depending on model

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Access rights based on private key authentication or shared access signatures

Role based authorization

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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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