DBMS > Apache Jena - TDB vs. Microsoft Azure Table Storage vs. MySQL vs. Solr

System Properties Comparison Apache Jena - TDB vs. Microsoft Azure Table Storage vs. MySQL vs. Solr

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Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

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

Widely used open source RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

RDF store

Wide column store

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

jena.apache.org/documentation/tdb/index.html

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

www.mysql.com

solr.apache.org

Technical documentation

jena.apache.org/documentation/tdb/index.html

dev.mysql.com/doc

solr.apache.org/resources.html

Developer

Apache Software Foundation

originally developed by HP Labs

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Initial release

2000

2012

1995

2006

Current release

4.9.0, July 2023

8.4.0, April 2024

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Java

Server operating systems

All OS with a Java VM

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

RDF Schemas

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RESTful HTTP/JSON API

Supported programming languages

Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

Java plugins

Triggers

yes

via event handler

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

TDB Transactions

optimistic locking

ACID

not for MyISAM storage engine

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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 control via Jena Security

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

yes

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