DBMS > Amazon Redshift vs. Apache Drill vs. CockroachDB

System Properties Comparison Amazon Redshift vs. Apache Drill 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

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

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

Document store
Relational DBMS

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	4.74
Rank	#67	Overall
	#36	Relational DBMS

Website

aws.amazon.com/redshift

drill.apache.org

www.cockroachlabs.com

Technical documentation

docs.aws.amazon.com/redshift

drill.apache.org/docs

www.cockroachlabs.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Cockroach Labs

Initial release

2012

2015

Current release

1.20.3, January 2023

24.1.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

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 SELECT statement is SQL:2003 compliant

yes, wire compatible with PostgreSQL

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

C++

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

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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

Role-based access control

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