DBMS > EventStoreDB vs. EXASOL vs. Hive vs. RDF4J

System Properties Comparison EventStoreDB vs. EXASOL vs. Hive vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

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

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

Primary database model

Event Store

Relational DBMS

RDF store

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

Technical documentation

developers.eventstore.com

www.exasol.com/resources

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

rdf4j.org/documentation

Developer

Event Store Limited

Exasol

Apache Software Foundation

initially developed by Facebook

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

Initial release

2012

2000

2012

2004

Current release

21.2, February 2021

3.1.3, April 2022

License

Commercial or Open Source

Open Source

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

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Implementation language

Java

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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

yes

SQL-like DML and DDL statements

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java
Lua
Python
R

C++
Java
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

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

Access rights for users, groups and roles

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