DBMS > Couchbase vs. CrateDB vs. Google BigQuery

System Properties Comparison Couchbase vs. CrateDB vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with a powerful search engine and in-built operational and analytical capabilities

Distributed Date Store based on Lucene

Large scale data warehouse service with append-only tables

Primary database model

Document store

Relational DBMS
Search engine

Relational DBMS

Secondary database models

Key-value store

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

using the Geocouch extension

Document store
Time Series DBMS

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

Score	28.38
Rank	#30	Overall
	#5	Document stores

Score	0.97
Rank	#178	Overall
	#86	Relational DBMS
	#13	Search engines

Score	48.61
Rank	#23	Overall
	#15	Relational DBMS

Website

www.couchbase.com

crate.io

cloud.google.com/bigquery

Technical documentation

docs.couchbase.com

crate.io/docs

cloud.google.com/bigquery/docs

Developer

Couchbase, Inc.

Crate

Google

Initial release

2011

2013

2010

Current release

Server: 7.0, July 2021; Mobile: 3, February 2022; Couchbase Capella, October 2021

License

Commercial or Open Source

Open Source

Apache version 2; Commercial licenses also available

Open Source

commercial

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 Capella: a fully managed database-as-a-service that eliminates database management efforts and reduces cost

Implementation language

C, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java 7 (and higher) VM

hosted

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

String, Boolean, Number

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++.

yes, but no triggers and constraints

yes

APIs and other access methods

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

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Scala

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

Functions and timers in JavaScript

user defined functions

in JavaScript

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

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

selectable on a per-operation basis

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

Since BigQuery is designed for querying data

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

User concepts

Access control

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

rights management via user accounts

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

Google Cloud Identity & Access Management (IAM)

More information provided by the system vendor

Specific characteristics

Developed as an alternative to traditionally inflexible relational databases, Couchbase...
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CrateDB is an open source distributed SQL database that spreads data and processing...
» more

Competitive advantages

Couchbase was architected with several differentiated capabilities: Shared-nothing,...
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CrateDB is typically used in operational analytics applications, particularly those...
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Typical application scenarios

Customer 360 for user profile, session store and data aggregation (Comcast, Equifax,...
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CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
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Key customers

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

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
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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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The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
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Licensing and pricing models

The Community Edition (CE) of Couchbase Server and Couchbase Mobile are available...
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CrateDB pricing CrateDB Community Edition is open source and free to use under the...
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