DBMS > BigObject vs. Blueflood vs. Cassandra vs. IBM Cloudant vs. RDFox

System Properties Comparison BigObject vs. Blueflood vs. Cassandra vs. IBM Cloudant vs. RDFox

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Database as a Service offering based on Apache CouchDB

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Vector DBMS

starting with release V5

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

bigobject.io

blueflood.io

cassandra.apache.org

www.ibm.com/products/cloudant

www.oxfordsemantic.tech

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

cassandra.apache.org/doc/latest

cloud.ibm.com/docs/Cloudant

docs.oxfordsemantic.tech

Developer

BigObject, Inc.

Rackspace

Apache Software Foundation

Apache top level project, originally developped by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oxford Semantic Technologies

Initial release

2015

2013

2008

2010

2017

Current release

4.1.3, July 2023

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Erlang

C++

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

BSD
Linux
OS X
Windows

hosted

Linux
macOS
Windows

Data scheme

yes

predefined scheme

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

RESTful HTTP/JSON API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
Java

Server-side scripts

Stored procedures

Lua

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

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

Atomicity and isolation are supported for single operations

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Optimistic locking

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 rights for users can be defined per object

Access rights for users can be defined per database

Roles, resources, and access types

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

An Introduction to David Jones-Gilardi, Developer Relations
11 June 2024

Introducing Tejas Kumar, Developer Relations Engineer
7 June 2024

Indexing All of Wikipedia on a Laptop
5 June 2024

An Introduction to Phil Nash, Developer Relations
3 June 2024

Focus on Creativity, Not Clusters: DataStax Mission Control in Action!
30 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.