DBMS > CouchDB vs. Dolt vs. VoltDB vs. XTDB

System Properties Comparison CouchDB vs. Dolt vs. VoltDB vs. XTDB

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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.

A MySQL compatible DBMS with Git-like versioning of data and schema

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store

Relational DBMS

Document store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

couchdb.apache.org

github.com/dolthub/dolt
www.dolthub.com

www.voltdb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.couchdb.org/en/stable

docs.dolthub.com

docs.voltdb.com

www.xtdb.com/docs

Developer

Apache Software Foundation

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

DoltHub Inc

VoltDB Inc.

Juxt Ltd.

Initial release

2005

2018

2010

2019

Current release

3.3.3, December 2023

11.3, April 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java, C++

Clojure

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
OS X

for development

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

only a subset of SQL 99

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP/JSON API

CLI Client
HTTP REST

Java API
JDBC
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

View functions in JavaScript

yes

currently in alpha release

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

atomic operations within a single document possible

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Only one user is configurable, and must be specified in the config file at startup

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

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Recent citations in the news

How to Automate A Blog Post App Deployment With GitHub Actions, Node.js, CouchDB, and Aptible
4 December 2023, hackernoon.com

How to install the CouchDB NoSQL database on Debian Server 11
16 June 2022, TechRepublic

IBM Cloudant pulls plan to fund new foundational layer for CouchDB
15 March 2022, The Register

CouchDB 3.0 ends admin party era • DEVCLASS
27 February 2020, DevClass

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27 February 2020, InfoWorld

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Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

Are you still not using Version Control for Data?
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16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

provided by Google News

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