DBMS > Apache Impala vs. Ehcache vs. OpenQM vs. RDF4J

System Properties Comparison Apache Impala vs. Ehcache vs. OpenQM vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A widely adopted Java cache with tiered storage options

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

impala.apache.org

www.ehcache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

rdf4j.org

Technical documentation

impala.apache.org/impala-docs.html

www.ehcache.org/documentation

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Terracotta Inc, owned by Software AG

Rocket Software, originally Martin Phillips

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

Initial release

2013

2009

1993

2004

Current release

4.1.0, June 2022

3.10.0, March 2022

3.4-12

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; commercial licenses available

Open Source

GPLv2, extended commercial license available

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

C++

Java

Server operating systems

Linux

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JCache

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC

Java

.Net
Basic
C
Java
Objective C
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

by using Terracotta Server

yes

none

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

Eventual Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

based on Apache Sentry and Kerberos

Access rights can be defined down to the item level

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More resources

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