DBMS > Amazon DocumentDB vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. NuoDB vs. SAP HANA

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. NuoDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

aws.amazon.com/documentdb

azure.microsoft.com/services/cosmos-db

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

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

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/documentdb/resources

learn.microsoft.com/azure/cosmos-db

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

doc.nuodb.com

help.sap.com/hana

Developer

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

SAP

Initial release

2019

2014

1989

2013

2010

Current release

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

JavaScript

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

Java, SQL

SQLScript, R

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

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

yes

User concepts

Access control

Access rights for users and roles

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

yes

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