DBMS > Amazon Redshift vs. Drizzle vs. GeoSpock

System Properties Comparison Amazon Redshift vs. Drizzle vs. GeoSpock

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Spatial and temporal data processing engine for extreme data scale

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Website

aws.amazon.com/redshift

geospock.com

Technical documentation

docs.aws.amazon.com/redshift

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

GeoSpock

Initial release

2012

2008

Current release

7.2.4, September 2012

2.0, September 2019

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Javascript

Server operating systems

hosted

FreeBSD
Linux
OS X

hosted

Data 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

with proprietary extensions

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC
ODBC

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per table

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