DBMS > Apache Kylin vs. eXtremeDB vs. HBase vs. RDF4J

System Properties Comparison Apache Kylin vs. eXtremeDB vs. HBase vs. RDF4J

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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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Wide-column store based on Apache Hadoop and on concepts of BigTable

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Wide column store

RDF store

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

Technical documentation

kylin.apache.org/docs

www.mcobject.com/docs/extremedb.htm

hbase.apache.org/book.html

rdf4j.org/documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

McObject

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2015

2001

2008

2004

Current release

3.1.0, July 2020

8.2, 2021

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

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 and C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free, schema definition possible

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

with the option: eXtremeSQL

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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