DBMS > Amazon Redshift vs. HyperSQL vs. MonetDB vs. QuestDB

System Properties Comparison Amazon Redshift vs. HyperSQL vs. MonetDB vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A relational database management system that stores data in columns

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

aws.amazon.com/redshift

hsqldb.org

www.monetdb.org

questdb.io

Technical documentation

docs.aws.amazon.com/redshift

hsqldb.org/web/hsqlDocsFrame.html

www.monetdb.org/Documentation

questdb.io/docs

Developer

Amazon (based on PostgreSQL)

MonetDB BV

QuestDB Technology Inc

Initial release

2012

2001

2004

2014

Current release

2.7.2, June 2023

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

Mozilla Public License 2.0

Open Source

Apache 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

Java (Zero-GC), C++, Rust

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

SQL with time-series extensions

APIs and other access methods

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC
Java

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

user defined functions

in Python

Java, SQL

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding via remote tables

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

ACID for single-table writes

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.

yes

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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