DBMS > Amazon Redshift vs. BigObject vs. Couchbase vs. Microsoft SQL Server vs. PouchDB

System Properties Comparison Amazon Redshift vs. BigObject vs. Couchbase vs. Microsoft SQL Server vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

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

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

Document store

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

Document store
Graph DBMS
Spatial DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

aws.amazon.com/redshift

bigobject.io

www.couchbase.com

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

pouchdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

docs.couchbase.com

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

pouchdb.com/guides

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Couchbase, Inc.

Microsoft

Apache Software Foundation

Initial release

2012

2015

2011

1989

2012

Current release

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

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

free community edition available

Open Source

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

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++, Go and Erlang

C++

JavaScript

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

restricted

yes

via views

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

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

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

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

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

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

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

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

View functions in JavaScript

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic Sharding

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

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

including cross data center replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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