DBMS > CouchDB vs. Microsoft SQL Server vs. OrigoDB vs. QuestDB vs. SwayDB

System Properties Comparison CouchDB vs. Microsoft SQL Server vs. OrigoDB vs. QuestDB vs. SwayDB

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.

Microsofts flagship relational DBMS

A fully ACID in-memory object graph database

A high performance open source SQL database for time series data

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

couchdb.apache.org

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

origodb.com

questdb.io

swaydb.simer.au

Technical documentation

docs.couchdb.org/en/stable

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

origodb.com/docs

questdb.io/docs

Developer

Apache Software Foundation

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

Microsoft

Robert Friberg et al

QuestDB Technology Inc

Simer Plaha

Initial release

2005

1989

2009

under the name LiveDB

2014

2018

Current release

3.3.3, December 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

C++

Java (Zero-GC), C++, Rust

Scala

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL with time-series extensions

APIs and other access methods

RESTful HTTP/JSON API

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

.NET Client API
HTTP API
LINQ

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

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

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

.Net

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Java
Kotlin
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

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

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

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

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning (by timestamps)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

Source-replica replication with eventual consistency

none

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

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

atomic operations within a single document possible

ACID

ACID for single-table writes

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

through memory mapped files

yes

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Role based authorization

More information provided by the system vendor

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