DBMS > CouchDB vs. Dolt vs. Impala

System Properties Comparison CouchDB vs. Dolt vs. Impala

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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

Analytic DBMS for Hadoop

Primary database model

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store

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

Score	17.16
Rank	#41	Overall
	#7	Document stores

Score	0.56
Rank	#230	Overall
	#110	Relational DBMS

Score	17.79
Rank	#40	Overall
	#25	Relational DBMS

Website

couchdb.apache.org

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

www.cloudera.com/products/open-source/apache-hadoop/impala.html

Technical documentation

docs.couchdb.org/en/stable

docs.dolthub.com

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

Developer

Apache Software Foundation

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

DoltHub Inc

Cloudera

Initial release

2005

2018

2013

Current release

3.2.2, April 2022

4.0.0, July 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

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

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

CLI Client
HTTP REST

JDBC
ODBC

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

All languages supporting JDBC/ODBC

Server-side scripts

Stored procedures

View functions in JavaScript

yes

currently in alpha release

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

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.

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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More resources

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