DBMS > Amazon Redshift vs. Apache Doris vs. Apache Phoenix vs. Blueflood vs. Hive

System Properties Comparison Amazon Redshift vs. Apache Doris vs. Apache Phoenix vs. Blueflood vs. Hive

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An MPP-based analytics DBMS embracing the MySQL protocol

A scale-out RDBMS with evolutionary schema built on Apache HBase

Scalable TimeSeries DBMS based on Cassandra

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

aws.amazon.com/redshift

doris.apache.org
github.com/apache/doris

phoenix.apache.org

blueflood.io

hive.apache.org

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

phoenix.apache.org

github.com/rax-maas/blueflood/wiki

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

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Rackspace

Apache Software Foundation

initially developed by Facebook

Initial release

2012

2017

2014

2013

2012

Current release

1.2.2, February 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache 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

Server operating systems

hosted

Linux

Linux
Unix
Windows

Linux
OS X

All OS with a Java VM

Data scheme

yes

late-bound, schema-on-read capabilities

predefined scheme

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

JDBC

HTTP REST

JDBC
ODBC
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users, groups and roles

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