DBMS > CouchDB vs. DolphinDB vs. MonetDB vs. OrigoDB vs. QuestDB

System Properties Comparison CouchDB vs. DolphinDB vs. MonetDB vs. OrigoDB vs. QuestDB

Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A relational database management system that stores data in columns

A fully ACID in-memory object graph database

A high performance open source SQL database for time series data

Primary database model

Document store

Time Series DBMS
Vector DBMS

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

Technical documentation

docs.couchdb.org/en/stable

docs.dolphindb.cn/en/help200/index.html

www.monetdb.org/Documentation

origodb.com/docs

questdb.io/docs

Developer

Apache Software Foundation

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

DolphinDB, Inc

MonetDB BV

Robert Friberg et al

QuestDB Technology Inc

Initial release

2005

2018

2004

2009

under the name LiveDB

2014

Current release

3.3.3, December 2023

v2.00.4, January 2022

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free community version available

Open Source

Mozilla Public License 2.0

Open Source

Apache 2.0

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

Erlang

C++

Java (Zero-GC), C++, Rust

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

SQL with time-series extensions

APIs and other access methods

RESTful HTTP/JSON API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

.NET Client API
HTTP API
LINQ

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

.Net

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

View functions in JavaScript

yes

yes, in SQL, C, R

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

horizontal partitioning

Sharding via remote tables

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Source-replica replication available in experimental status

Source-replica replication

Source-replica replication with eventual consistency

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

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

atomic operations within a single document possible

yes

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

through memory mapped files

User concepts

Access control

Access rights for users can be defined per database

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Role based authorization

More information provided by the system vendor

News

Combine Java and Rust Code Coverage in a Polyglot Project
10 September 2024

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4 September 2024

Building a new vector based storage model
22 August 2024

Calibrating VWAP executions with QuestDB and Grafana
16 August 2024

Write Time: a call for community writers
13 August 2024

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