DBMS > Amazon DocumentDB vs. CouchDB vs. HBase vs. Microsoft SQL Server vs. Oracle

System Properties Comparison Amazon DocumentDB vs. CouchDB vs. HBase vs. Microsoft SQL Server vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Microsofts flagship relational DBMS

Widely used RDBMS

Primary database model

Document store

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

aws.amazon.com/documentdb

couchdb.apache.org

hbase.apache.org

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

www.oracle.com/database

Technical documentation

aws.amazon.com/documentdb/resources

docs.couchdb.org/en/stable

hbase.apache.org/book.html

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

docs.oracle.com/en/database

Developer

Apache Software Foundation

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

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Oracle

Initial release

2019

2005

2008

1989

1980

Current release

3.3.3, December 2023

2.3.4, January 2021

SQL Server 2022, November 2022

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache version 2

commercial

restricted free version is available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

Java

C++

C and C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

schema-free, schema definition possible

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP/JSON API

Java API
RESTful HTTP API
Thrift

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Coprocessors in Java

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

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

improved architecture with release 2.0

Sharding

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

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

atomic operations within a single document possible

Single row ACID (across millions of columns)

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles

Access rights for users can be defined per database

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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