DBMS > CouchDB vs. Google BigQuery vs. Microsoft SQL Server vs. NuoDB vs. ToroDB

System Properties Comparison CouchDB vs. Google BigQuery vs. Microsoft SQL Server vs. NuoDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Large scale data warehouse service with append-only tables

Microsofts flagship relational DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store

Relational DBMS

Document store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

couchdb.apache.org

cloud.google.com/bigquery

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

www.3ds.com/nuodb-distributed-sql-database

github.com/torodb/server

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigquery/docs

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

doc.nuodb.com

Developer

Apache Software Foundation

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

Google

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

8Kdata

Initial release

2005

2010

1989

2013

2016

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

commercial

limited edition free

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

C++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

APIs and other access methods

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

in JavaScript

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

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

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

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

Source-replica replication

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

Eventual Consistency
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

Since BigQuery is designed for querying data

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

MVCC

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

Temporary table

User concepts

Access control

Access rights for users can be defined per database

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Access rights for users and roles

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