DBMS > BigObject vs. Blueflood vs. RDFox vs. ReductStore

System Properties Comparison BigObject vs. Blueflood vs. RDFox vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

High performance knowledge graph and semantic reasoning engine

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Graph DBMS
RDF store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

bigobject.io

blueflood.io

www.oxfordsemantic.tech

github.com/reductstore
www.reduct.store

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

docs.oxfordsemantic.tech

www.reduct.store/docs

Developer

BigObject, Inc.

Rackspace

Oxford Semantic Technologies

ReductStore LLC

Initial release

2015

2013

2017

2023

Current release

6.0, Septermber 2022

1.9, March 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

Open Source

Business Source License 1.1

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++

C++, Rust

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
macOS
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

predefined scheme

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

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

RESTful HTTP API
SPARQL 1.1

HTTP API

Supported programming languages

C
Java

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Roles, resources, and access types

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