DBMS > BaseX vs. Blueflood vs. Faircom EDGE vs. RDF4J vs. SAP Advantage Database Server

System Properties Comparison BaseX vs. Blueflood vs. Faircom EDGE vs. RDF4J vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Scalable TimeSeries DBMS based on Cassandra

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Native XML DBMS

Time Series DBMS

Key-value store
Relational DBMS

RDF store

Relational DBMS

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

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

basex.org

blueflood.io

www.faircom.com/products/faircom-edge

rdf4j.org

www.sap.com/products/advantage-database-server.html

Technical documentation

docs.basex.org

github.com/rax-maas/blueflood/wiki

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

rdf4j.org/documentation

Developer

BaseX GmbH

Rackspace

FairCom Corporation

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

Sybase, SAP

Initial release

2007

2013

1979

2004

1993

Current release

11.2, August 2024

V3, October 2020

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

Java

ANSI C, C++

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Unix
Windows

Linux
Windows

Data scheme

schema-free

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

yes, ANSI Standard SQL Types

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

yes

ANSI SQL queries

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

HTTP REST

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Java
PHP
Python

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

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
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

multiple readers, single writer

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

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

caching of (temporary) tables can be configured

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

fine grained access rights according to SQL-standard

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