DBMS > Alibaba Cloud Table Store vs. DataFS vs. EsgynDB vs. JaguarDB vs. PouchDB

System Properties Comparison Alibaba Cloud Table Store vs. DataFS vs. EsgynDB vs. JaguarDB vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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.

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

Performant, highly scalable DBMS for AI and IoT applications

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Wide column store

Object oriented DBMS

Relational DBMS

Key-value store
Vector DBMS

Document store

Secondary database models

Graph DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

dev.mobiland.com/Overview.xsp

www.jaguardb.com/support.html

pouchdb.com/guides

Developer

Alibaba

Mobiland AG

Esgyn

DataJaguar, Inc.

Apache Software Foundation

Initial release

2016

2018

2015

2012

Current release

1.1.263, October 2022

3.3 July 2023

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

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

C++, Java

C++

the server part. Clients available in other languages

JavaScript

Server operating systems

hosted

Windows

Linux

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

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

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

via views

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

HTTP API

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java
Python

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

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

JavaScript

Server-side scripts

Stored procedures

Java 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

Sharding

Implicit feature of the cloud service

Proprietary Sharding system

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication between multi datacenters

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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 subaccounts and tokens

Windows-Profile

fine grained access rights according to SQL-standard

rights management via user accounts

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More resources

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