DBMS > Apache Drill vs. Drizzle vs. PostGIS

System Properties Comparison Apache Drill vs. Drizzle vs. PostGIS

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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.

Description

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

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

Spatial extension of PostgreSQL

Primary database model

Document store
Relational DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.82
Rank	#128	Overall
	#24	Document stores
	#60	Relational DBMS

Score	19.44
Rank	#29	Overall
	#1	Spatial DBMS

Website

drill.apache.org

postgis.net

Technical documentation

drill.apache.org/docs

postgis.net/documentation

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Initial release

2012

2008

2005

Current release

1.20.3, January 2023

7.2.4, September 2012

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

Supported programming languages

C++

C
C++
Java
PHP

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

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

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.

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Update Apache Drill Eliminates ETL, Data Transformation for MapR Database
30 March 2022, InApps Technology

Interacting with MapR-DB
11 December 2018, hackernoon.com

provided by Google News

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