DBMS > Apache Kylin vs. DuckDB vs. HyperSQL vs. YottaDB

System Properties Comparison Apache Kylin vs. DuckDB vs. HyperSQL vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

Technical documentation

kylin.apache.org/docs

duckdb.org/docs

hsqldb.org/web/hsqlDocsFrame.html

yottadb.com/resources/documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

YottaDB, LLC

Initial release

2015

2018

2001

Current release

3.1.0, July 2020

1.0.0, June 2024

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

based on BSD license

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

Linux

server-less

All OS with a Java VM

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

Docker
Linux

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

All languages supporting JDBC/ODBC
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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

User concepts

Access control

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

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