DBMS > Blueflood vs. dBASE vs. Microsoft Azure Table Storage vs. RDF4J

System Properties Comparison Blueflood vs. dBASE vs. Microsoft Azure Table Storage vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

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.

Primary database model

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

blueflood.io

www.dbase.com

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

rdf4j.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.dbase.com/support/knowledgebase

rdf4j.org/documentation

Developer

Rackspace

Asthon Tate

Microsoft

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

Initial release

2013

1979

2012

2004

Current release

dBASE 2019, 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
OS X
Unix
Windows

Data scheme

predefined scheme

yes

schema-free

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

APIs and other access methods

HTTP REST

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

dBase proprietary IDE

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

Java
PHP
Python

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

optimistic locking

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.

User concepts

Access control

Access rights for users and roles

Access rights based on private key authentication or shared access signatures

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