DBMS > Apache Kylin vs. EXASOL vs. RDF4J vs. Riak KV vs. SQLite

System Properties Comparison Apache Kylin vs. EXASOL vs. RDF4J vs. Riak KV vs. SQLite

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Distributed, fault tolerant key-value store

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

RDF store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

kylin.apache.org/docs

www.exasol.com/resources

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

www.sqlite.org/docs.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

Exasol

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

OpenSource, formerly Basho Technologies

Dwayne Richard Hipp

Initial release

2015

2000

2004

2009

2000

Current release

3.1.0, July 2020

3.2.0, December 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
OS X

server-less

Data scheme

yes

RDF Schemas

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
Lua
Python
R

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Access rights for users, groups and roles according to SQL-standard

yes, using Riak Security

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