DBMS > Apache Impala vs. RDF4J vs. SiteWhere vs. TerminusDB

System Properties Comparison Apache Impala vs. RDF4J vs. SiteWhere vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

M2M integration platform for persisting/querying time series data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store

Document store
RDF store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

impala.apache.org

rdf4j.org

github.com/sitewhere/sitewhere

terminusdb.com

Technical documentation

impala.apache.org/impala-docs.html

rdf4j.org/documentation

sitewhere1.sitewhere.io/index.html

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

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

SiteWhere

DataChemist Ltd.

Initial release

2013

2004

2010

2018

Current release

4.1.0, June 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Common Public Attribution License Version 1.0

Open Source

GPL V3

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

C++

Java

Prolog, Rust

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

RDF Schemas

predefined scheme

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

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

based on HBase

Journaling Streams

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

Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

in-memory journaling

In-memory capabilities

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept

Role-based access control

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More resources

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