DBMS > Blueflood vs. EsgynDB vs. EXASOL vs. Oracle NoSQL vs. RDF4J

System Properties Comparison Blueflood vs. EsgynDB vs. EXASOL vs. Oracle NoSQL vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Primary database model

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

RDF store

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

blueflood.io

www.esgyn.cn

www.exasol.com

www.oracle.com/database/nosql/technologies/nosql

rdf4j.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.exasol.com/resources

docs.oracle.com/en/database/other-databases/nosql-database/index.html

rdf4j.org/documentation

Developer

Rackspace

Esgyn

Exasol

Oracle

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

Initial release

2013

2015

2000

2011

2004

Current release

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++, Java

Java

Server operating systems

Linux
OS X

Linux

Linux
Solaris SPARC/x86

Linux
OS X
Unix
Windows

Data scheme

predefined scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

optional

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

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
Lua
Python
R

C
C#
Go
Java
JavaScript (Node.js)
Python

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication between multi datacenters

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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.

yes

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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