DBMS > Amazon Redshift vs. Apache Drill vs. KairosDB vs. MonetDB vs. RethinkDB

System Properties Comparison Amazon Redshift vs. Apache Drill vs. KairosDB vs. MonetDB vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Distributed Time Series DBMS based on Cassandra or H2

A relational database management system that stores data in columns

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Relational DBMS

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

aws.amazon.com/redshift

drill.apache.org

github.com/kairosdb/kairosdb

www.monetdb.org

rethinkdb.com

Technical documentation

docs.aws.amazon.com/redshift

drill.apache.org/docs

kairosdb.github.io

www.monetdb.org/Documentation

rethinkdb.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

MonetDB BV

The Linux Foundation

since July 2017

Initial release

2012

2013

2004

2009

Current release

1.20.3, January 2023

1.2.2, November 2018

Dec2023 (11.49), December 2023

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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 SELECT statement is SQL:2003 compliant

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C++

Java
JavaScript

Node.js
PHP
Python

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes, in SQL, C, R

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding via remote tables

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

none

Source-replica replication available in experimental status

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

User concepts

Access control

fine grained access rights according to SQL-standard

Depending on the underlying data source

simple password-based access control

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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