DBMS > Amazon DynamoDB vs. Kyligence Enterprise vs. Microsoft Azure SQL Database vs. MonetDB

System Properties Comparison Amazon DynamoDB vs. Kyligence Enterprise vs. Microsoft Azure SQL Database vs. MonetDB

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A distributed analytics engine for big data, built on top of Apache Kylin

Database as a Service offering with high compatibility to Microsoft SQL Server

A relational database management system that stores data in columns

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

aws.amazon.com/dynamodb

kyligence.io/kyligence-enterprise

azure.microsoft.com/en-us/products/azure-sql/database

www.monetdb.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.microsoft.com/en-us/azure/azure-sql

www.monetdb.org/Documentation

Developer

Amazon

Kyligence, Inc.

Microsoft

MonetDB BV

Initial release

2012

2016

2010

2004

Current release

V12

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Mozilla Public License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

hosted

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

Transact SQL

yes, in SQL, C, R

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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