DBMS > CouchDB vs. H2 vs. HEAVY.AI vs. Lovefield

System Properties Comparison CouchDB vs. H2 vs. HEAVY.AI vs. Lovefield

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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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

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

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Website

couchdb.apache.org

www.h2database.com

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

Technical documentation

docs.couchdb.org/en/stable

www.h2database.com/html/main.html

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation

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

Thomas Mueller

HEAVY.AI, Inc.

Google

Initial release

2005

2016

2014

Current release

3.3.3, December 2023

2.2.220, July 2023

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2; enterprise edition available

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

Java

C++ and CUDA

JavaScript

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

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 query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

Supported programming languages

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

Java

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

View functions in JavaScript

Java Stored Procedures and User-Defined Functions

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

none

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

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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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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