DBMS > Amazon Redshift vs. Apache Druid vs. IBM Db2 vs. NuoDB vs. Rockset

System Properties Comparison Amazon Redshift vs. Apache Druid vs. IBM Db2 vs. NuoDB vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Common in IBM host environments, 2 different versions for host and Windows/Linux

NuoDB is a webscale distributed database that supports SQL and ACID transactions

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Document store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Relational DBMS
Search engine

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	123.05
Rank	#9	Overall
	#6	Relational DBMS

Score	0.87
Rank	#201	Overall
	#94	Relational DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Website

aws.amazon.com/redshift

druid.apache.org

www.ibm.com/products/db2

www.3ds.com/nuodb-distributed-sql-database

rockset.com

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

www.ibm.com/docs/en/db2

doc.nuodb.com

docs.rockset.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

IBM

Dassault Systèmes

originally NuoDB, Inc.

Rockset

Initial release

2012

1983

host version

2013

2019

Current release

30.0.0, June 2024

12.1, October 2016

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

free version is available

commercial

limited edition free

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.

Implementation language

Java

C and C++

C++

Server operating systems

hosted

Linux
OS X
Unix

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

hosted

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

restricted

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

only with Windows/Unix/Linux Version

data is dynamically stored/cached on the nodes where it is read/written

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

yes

with separate tools (MQ, InfoSphere)

yes

Managed transparently by NuoDB

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Access rights for users and organizations can be defined via Rockset console

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