DBMS > CouchDB vs. Linter vs. Microsoft Azure Table Storage vs. TigerGraph vs. ToroDB

System Properties Comparison CouchDB vs. Linter vs. Microsoft Azure Table Storage vs. TigerGraph vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

RDBMS for high security requirements

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

couchdb.apache.org

linter.ru

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

www.tigergraph.com

github.com/torodb/server

Technical documentation

docs.couchdb.org/en/stable

docs.tigergraph.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

relex.ru

Microsoft

8Kdata

Initial release

2005

1990

2012

2017

2016

Current release

3.3.3, December 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

AGPL-V3

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

Erlang

C and C++

C++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

Linux

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

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

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

atomic operations within a single document possible

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Role-based access control

Access rights for users and roles

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More resources

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