DBMS > CouchDB vs. Dgraph vs. Google BigQuery vs. Graphite

System Properties Comparison CouchDB vs. Dgraph vs. Google BigQuery vs. Graphite

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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.

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Website

couchdb.apache.org

dgraph.io

cloud.google.com/bigquery

github.com/graphite-project/graphite-web

Technical documentation

docs.couchdb.org/en/stable

dgraph.io/docs

cloud.google.com/bigquery/docs

graphite.readthedocs.io

Developer

Apache Software Foundation

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

Dgraph Labs, Inc.

Google

Chris Davis

Initial release

2005

2016

2010

2006

Current release

3.3.3, December 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

Python

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Linux
Unix

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

APIs and other access methods

RESTful HTTP/JSON API

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

RESTful HTTP/JSON API

HTTP API
Sockets

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication via Raft

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

none

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a single document possible

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

locking

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

Planned for future releases

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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