DBMS > CouchDB vs. Google Cloud Bigtable vs. Graphite vs. PouchDB vs. RocksDB

System Properties Comparison CouchDB vs. Google Cloud Bigtable vs. Graphite vs. PouchDB vs. RocksDB

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Key-value store
Wide column store

Time Series DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

couchdb.apache.org

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

pouchdb.com

rocksdb.org

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigtable/docs

graphite.readthedocs.io

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

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

Google

Chris Davis

Apache Software Foundation

Facebook, Inc.

Initial release

2005

2015

2006

2012

2013

Current release

3.3.3, December 2023

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Python

JavaScript

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
Unix

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

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

via views

SQL

Support of SQL

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Sockets

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

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)
Python

JavaScript (Node.js)
Python

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a single document possible

Atomic single-row operations

yes

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

locking

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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 based on Google Cloud Identity and Access Management (IAM)

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