DBMS > Apache Kylin vs. DataFS vs. Hive vs. VelocityDB

System Properties Comparison Apache Kylin vs. DataFS vs. Hive vs. VelocityDB

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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

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

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	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

kylin.apache.org/docs

dev.mobiland.com/Overview.xsp

cwiki.apache.org/confluence/display/Hive/Home

velocitydb.com/UserGuide

Developer

Apache Software Foundation, originally contributed from eBay Inc

Mobiland AG

Apache Software Foundation

initially developed by Facebook

VelocityDB Inc

Initial release

2015

2018

2012

2011

Current release

3.1.0, July 2020

1.1.263, October 2022

3.1.3, April 2022

7.x

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2

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

Server operating systems

Linux

Windows

All OS with a Java VM

Any that supports .NET

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

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)

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

JDBC
ODBC
Thrift

.Net

Supported programming languages

.Net
C
C#
C++
VB.Net

C++
Java
PHP
Python

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

no, except callback-events from server when changes happened

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

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

Access rights for users, groups and roles

Based on Windows Authentication

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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