DBMS > Couchbase vs. Google Cloud Datastore vs. Percona Server for MongoDB

System Properties Comparison Couchbase vs. Google Cloud Datastore vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines

Name

Description

JSON-based document store derived from CouchDB with a Memcached-compatible interface

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Document store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension

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

Score	30.76
Rank	#26	Overall
	#4	Document stores

Score	4.35
Rank	#79	Overall
	#11	Document stores

Score	0.71
Rank	#203	Overall
	#31	Document stores

Website

www.couchbase.com

cloud.google.com/datastore

www.percona.com/software/mongodb/percona-server-for-mongodb

Technical documentation

docs.couchbase.com

cloud.google.com/datastore/docs

www.percona.com/doc/percona-server-for-mongodb/LATEST/index.html

Developer

Couchbase, Inc.

Google

Percona

Initial release

2011

2008

2015

Current release

Server: 6.5, January 2020; Mobile: 2.7, January 2020; Couchbase Autonomous Operator: 1.2, May 2019

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache version 2; Commercial licenses also available

commercial

Open Source

GPL Version 2

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.

Couchbase Cloud: Deploy, manage, and operate Couchbase in a few clicks

Implementation language

C, C++, Go and Erlang

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

String, Boolean, Number

yes, details here

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

SQL

Support of SQL

Declarative query language (N1QL) that extends ANSI SQL to JSON. First commercial implementation of SQL++.

SQL-like query language (GQL)

APIs and other access methods

Native language bindings for CRUD, Query, Search and Analytics APIs

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

proprietary protocol using JSON

Supported programming languages

.Net
C
Clojure
ColdFusion
Erlang
Go
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala
Tcl

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

Functions and timers in JavaScript

using Google App Engine

JavaScript

Triggers

yes

via the TAP protocol

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication using Paxos

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

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.

yes

Ephemeral buckets

yes

via In-Memory Engine

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Developed as an alternative to traditionally inflexible relational databases, Couchbase...
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Competitive advantages

Couchbase was architected with several differentiated capabilities: Shared-nothing,...
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Typical application scenarios

Customer 360 for user profile, session store and data aggregation (Comcast, Equifax,...
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Key customers

Amadeus, AT&T, BD (Becton, Dickinson and Company), Carrefour, Cisco, Comcast, Disney,...
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Market metrics

Named a leader in the Forrester Wave™: Big Data NoSQL, Q1 2019 Over 10M downloads...
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Licensing and pricing models

The Community Edition (CE) of Couchbase Server and Couchbase Mobile are available...
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