DBMS > CouchDB vs. Firebase Realtime Database vs. InfluxDB vs. Microsoft SQL Server vs. TimescaleDB

System Properties Comparison CouchDB vs. Firebase Realtime Database vs. InfluxDB vs. Microsoft SQL Server vs. TimescaleDB

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.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

DBMS for storing time series, events and metrics

Microsofts flagship relational DBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

with GEO package

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

couchdb.apache.org

firebase.google.com/products/realtime-database

www.influxdata.com/products/influxdb-overview

www.microsoft.com/en-us/sql-server

www.timescale.com

Technical documentation

docs.couchdb.org/en/stable

firebase.google.com/docs/database

docs.influxdata.com/influxdb

learn.microsoft.com/en-US/sql/sql-server

docs.timescale.com

Developer

Apache Software Foundation

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

Google

acquired by Google 2014

Microsoft

Timescale

Initial release

2005

2012

2013

1989

2017

Current release

3.3.3, December 2023

2.7.6, April 2024

SQL Server 2022, November 2022

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X

through Homebrew

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
JSON over UDP

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

Java
JavaScript
Objective-C

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

limited functionality with using 'rules'

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

in enterprise version only

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

yes, but depending on the SQL-Server Edition

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

yes

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

Depending on used storage engine

yes

User concepts

Access control

Access rights for users can be defined per database

yes, based on authentication and database rules

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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