DBMS > Couchbase vs. CouchDB vs. EXASOL vs. InfluxDB vs. Snowflake

System Properties Comparison Couchbase vs. CouchDB vs. EXASOL vs. InfluxDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

DBMS for storing time series, events and metrics

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Key-value store

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

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

using the Geocouch extension

Spatial DBMS

with GEO package

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.couchbase.com

couchdb.apache.org

www.exasol.com

www.influxdata.com/products/influxdb-overview

www.snowflake.com

Technical documentation

docs.couchbase.com

docs.couchdb.org/en/stable

www.exasol.com/resources

docs.influxdata.com/influxdb

docs.snowflake.net/manuals/index.html

Developer

Couchbase, Inc.

Apache Software Foundation

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

Exasol

Snowflake Computing Inc.

Initial release

2011

2005

2000

2013

2014

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.3.3, December 2023

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache version 2

commercial

Open Source

MIT-License; commercial enterprise version available

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.

Implementation language

C, C++, Go and Erlang

Erlang

Server operating systems

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

SQL-like query language

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP/JSON API

.Net
JDBC
ODBC
WebSocket

HTTP API
JSON over UDP

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Java
Lua
Python
R

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

View functions in JavaScript

user defined functions

Triggers

yes

via the TAP protocol

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

improved architecture with release 2.0

Sharding

in enterprise version only

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

Depending on used storage engine

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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