DBMS > Amazon Redshift vs. JSqlDb vs. Microsoft Azure Cosmos DB vs. MonetDB vs. NSDb

System Properties Comparison Amazon Redshift vs. JSqlDb vs. Microsoft Azure Cosmos DB vs. MonetDB vs. NSDb

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

JavaScript Query Language Database, stores JavaScript objects and primitives

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/redshift

jsqldb.org (offline)

azure.microsoft.com/services/cosmos-db

www.monetdb.org

nsdb.io

Technical documentation

docs.aws.amazon.com/redshift

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

nsdb.io/Architecture

Developer

Amazon (based on PostgreSQL)

Konrad von Backstrom

Microsoft

MonetDB BV

Initial release

2012

2018

2014

2004

2017

Current release

0.8, December 2018

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

Server operating systems

hosted

Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

yes: int, bigint, decimal, string

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.

Secondary indexes

restricted

yes

All properties auto-indexed by default

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL 2003 with some extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript

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

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

Java
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

functions in JavaScript

JavaScript

yes, in SQL, C, R

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

Using Apache Lucene

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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