DBMS > Amazon Redshift vs. Apache Druid vs. CockroachDB

System Properties Comparison Amazon Redshift vs. Apache Druid vs. CockroachDB

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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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	14.52
Rank	#38	Overall
	#23	Relational DBMS

Score	2.92
Rank	#86	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	4.29
Rank	#66	Overall
	#36	Relational DBMS

Website

aws.amazon.com/redshift

druid.apache.org

www.cockroachlabs.com

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

www.cockroachlabs.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Cockroach Labs

Initial release

2012

2015

Current release

30.0.0, June 2024

24.1.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache 2.0, commercial license available

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

Server operating systems

hosted

Linux
OS X
Unix

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

dynamic schema

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

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

yes, wire compatible with PostgreSQL

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Multi-source replication using RAFT

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

In-memory capabilities

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

yes

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

Role-based access control

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