DBMS > CouchDB vs. Hive vs. LevelDB vs. openGauss vs. SQLite

System Properties Comparison CouchDB vs. Hive vs. LevelDB vs. openGauss vs. SQLite

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

couchdb.apache.org

hive.apache.org

github.com/google/leveldb

gitee.com/opengauss
opengauss.org

www.sqlite.org

Technical documentation

docs.couchdb.org/en/stable

cwiki.apache.org/confluence/display/Hive/Home

github.com/google/leveldb/blob/main/doc/index.md

docs.opengauss.org/en
gitee.com/opengauss/docs

www.sqlite.org/docs.html

Developer

Apache Software Foundation

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

Apache Software Foundation

initially developed by Facebook

Google

Huawei and openGauss community

Dwayne Richard Hipp

Initial release

2005

2012

2011

2019

2000

Current release

3.3.3, December 2023

3.1.3, April 2022

1.23, February 2021

3.0, March 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2

Open Source

BSD

Open Source

Public Domain

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++

C, C++, Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like DML and DDL statements

ANSI SQL 2011

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C++
Java
PHP
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

none

Source-replica replication

none

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

Immediate 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

via file-system locks

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

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 for users can be defined per database

Access rights for users, groups and roles

Access rights for users, groups and roles according to SQL-standard

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