DBMS > Amazon Redshift vs. HyperSQL vs. Kyligence Enterprise

System Properties Comparison Amazon Redshift vs. HyperSQL vs. Kyligence Enterprise

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

Primary database model

Relational DBMS

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Website

aws.amazon.com/redshift

hsqldb.org

kyligence.io/kyligence-enterprise

Technical documentation

docs.aws.amazon.com/redshift

hsqldb.org/web/hsqlDocsFrame.html

Developer

Amazon (based on PostgreSQL)

Kyligence, Inc.

Initial release

2012

2001

2016

Current release

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

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

Server operating systems

hosted

All OS with a Java VM

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

Linux

Data scheme

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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