DBMS > Amazon Redshift vs. BigchainDB vs. InfluxDB vs. MonetDB

System Properties Comparison Amazon Redshift vs. BigchainDB vs. InfluxDB vs. MonetDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

DBMS for storing time series, events and metrics

A relational database management system that stores data in columns

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Website

aws.amazon.com/redshift

www.bigchaindb.com

www.influxdata.com/products/influxdb-overview

www.monetdb.org

Technical documentation

docs.aws.amazon.com/redshift

bigchaindb.readthedocs.io/en/latest

docs.influxdata.com/influxdb

www.monetdb.org/Documentation

Developer

Amazon (based on PostgreSQL)

MonetDB BV

Initial release

2012

2016

2013

2004

Current release

2.7.5, January 2024

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

MIT-License; commercial enterprise version available

Open Source

Mozilla Public License 2.0

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.

Implementation language

Python

Server operating systems

hosted

Linux

Linux
OS X

through Homebrew

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

HTTP API
JSON over UDP

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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.

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

yes

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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