DBMS > Apache Kylin vs. DataFS vs. DuckDB vs. Hypertable vs. Yaacomo

System Properties Comparison Apache Kylin vs. DataFS vs. DuckDB vs. Hypertable vs. Yaacomo

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

An open source BigTable implementation based on distributed file systems such as Hadoop

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Graph DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Website

kylin.apache.org

newdatabase.com

duckdb.org

yaacomo.com

Technical documentation

kylin.apache.org/docs

dev.mobiland.com/Overview.xsp

duckdb.org/docs

Developer

Apache Software Foundation, originally contributed from eBay Inc

Mobiland AG

Hypertable Inc.

Q2WEB GmbH

Initial release

2015

2018

2009

Current release

3.1.0, July 2020

1.1.263, October 2022

0.10, February 2024

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

Open Source

GNU version 3. Commercial license available

commercial

Cloud-based only

Only available as a cloud service

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

Linux

Windows

server-less

Linux
OS X
Windows

an inofficial Windows port is available

Android
Linux
Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

C++ API
Thrift

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

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

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor on file system level

Source-replica replication

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

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

Windows-Profile

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

Introducing Kyligence Copilot: The AI Copilot for Data to Excel Your KPIs
23 August 2023, insideBIGDATA

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

eBay's Kylin Becomes a Top-Level Apache Open Source Project
9 December 2015, eBay Inc.

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services
9 November 2022, AWS Blog

provided by Google News

DuckDB 1.0 Released
4 June 2024, iProgrammer

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

provided by Google News

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