DBMS > CouchDB vs. Dgraph vs. HugeGraph vs. Lovefield vs. Riak KV

System Properties Comparison CouchDB vs. Dgraph vs. HugeGraph vs. Lovefield vs. Riak KV

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.

Distributed and scalable native Graph DBMS

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

couchdb.apache.org

dgraph.io

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

Technical documentation

docs.couchdb.org/en/stable

dgraph.io/docs

hugegraph.apache.org/docs

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

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Apache Software Foundation

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

Dgraph Labs, Inc.

Baidu

Google

OpenSource, formerly Basho Technologies

Initial release

2005

2016

2018

2014

2009

Current release

3.3.3, December 2023

0.9

2.1.12, February 2017

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

JavaScript

Erlang

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
macOS
Unix

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X

Data scheme

schema-free

yes

schema-free

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

also supports composite index and range index

yes

restricted

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP/JSON API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
Native Erlang Interface

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 (Node.js)
PHP
Python
Ruby

Groovy
Java
Python

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

View functions in JavaScript

asynchronous Gremlin script jobs

Erlang

Triggers

yes

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication via Raft

yes

depending on used storage backend, e.g. Cassandra and HBase

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

links between data sets can be stored

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

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

yes

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

Planned for future releases

Users, roles and permissions

yes, using Riak Security

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More resources

DB-Engines blog posts

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