DBMS > Amazon Redshift vs. CockroachDB vs. Hive

System Properties Comparison Amazon Redshift vs. CockroachDB vs. Hive

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

aws.amazon.com/redshift

www.cockroachlabs.com

hive.apache.org

Technical documentation

docs.aws.amazon.com/redshift

www.cockroachlabs.com/docs

cwiki.apache.org/confluence/display/Hive/Home

Developer

Amazon (based on PostgreSQL)

Cockroach Labs

Apache Software Foundation

initially developed by Facebook

Initial release

2012

2015

2012

Current release

23.1.1, May 2023

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

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

Server operating systems

hosted

Linux
macOS
Windows

All OS with a Java VM

Data scheme

yes

dynamic schema

yes

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

yes, wire compatible with PostgreSQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC

JDBC
ODBC
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

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

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

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

Role-based access control

Access rights for users, groups and roles

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