DBMS > Apache Impala vs. Microsoft Azure Table Storage vs. RDF4J vs. RRDtool

System Properties Comparison Apache Impala vs. Microsoft Azure Table Storage vs. RDF4J vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A Wide Column Store for rapid development using massive semi-structured datasets

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

impala.apache.org

azure.microsoft.com/en-us/services/storage/tables

rdf4j.org

oss.oetiker.ch/rrdtool

Technical documentation

impala.apache.org/impala-docs.html

rdf4j.org/documentation

oss.oetiker.ch/rrdtool/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

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

Tobias Oetiker

Initial release

2013

2012

2004

1999

Current release

4.1.0, June 2022

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

hosted

Linux
OS X
Unix
Windows

HP-UX
Linux

Data scheme

yes

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

in-process shared library
Pipes

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

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

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

based on Apache Sentry and Kerberos

Access rights based on private key authentication or shared access signatures

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More resources

DB-Engines blog posts

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