DBMS > Amazon Redshift vs. Apache Doris vs. Blueflood vs. GeoSpock

System Properties Comparison Amazon Redshift vs. Apache Doris vs. Blueflood vs. GeoSpock

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

An MPP-based analytics DBMS embracing the MySQL protocol

Scalable TimeSeries DBMS based on Cassandra

Spatial and temporal data processing engine for extreme data scale

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Website

aws.amazon.com/redshift

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

blueflood.io

geospock.com

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

github.com/rax-maas/blueflood/wiki

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

Rackspace

GeoSpock

Initial release

2012

2017

2013

Current release

1.2.2, February 2023

2.0, September 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Java, Javascript

Server operating systems

hosted

Linux

Linux
OS X

hosted

Data scheme

yes

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

temporal, categorical

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

HTTP REST

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

Sharding

based on Cassandra

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate 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 rights for users can be defined per table

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