DBMS > BigchainDB vs. Cassandra vs. Google BigQuery vs. IBM Cloudant vs. mSQL

System Properties Comparison BigchainDB vs. Cassandra vs. Google BigQuery vs. IBM Cloudant vs. mSQL

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

www.bigchaindb.com

cassandra.apache.org

cloud.google.com/bigquery

www.ibm.com/products/cloudant

hughestech.com.au/products/msql

Technical documentation

bigchaindb.readthedocs.io/en/latest

cassandra.apache.org/doc/latest

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Hughes Technologies

Initial release

2016

2008

2010

1994

Current release

4.1.3, July 2023

4.4, October 2021

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache version 2

commercial

free licenses can be provided

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

Python

Java

Erlang

Server operating systems

Linux

BSD
Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

yes

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

CLI Client
RESTful HTTP API

Proprietary protocol

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

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

Since BigQuery is designed for querying data

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

Access rights for users can be defined per object

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

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