DBMS > Apache Drill vs. Drizzle vs. HyperSQL vs. Realm

System Properties Comparison Apache Drill vs. Drizzle vs. HyperSQL vs. Realm

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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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

drill.apache.org

hsqldb.org

realm.io

Technical documentation

drill.apache.org/docs

hsqldb.org/web/hsqlDocsFrame.html

realm.io/docs

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Realm, acquired by MongoDB in May 2019

Initial release

2012

2008

2001

2014

Current release

1.20.3, January 2023

7.2.4, September 2012

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

based on BSD license

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Android
Backend: server-less
iOS
Windows

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.

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C++

C
C++
Java
PHP

All languages supporting JDBC/ODBC
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

Java, SQL

runs within the applications so server-side scripts are unnecessary

Triggers

hooks for callbacks inside the server can be used.

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

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

yes

In-Memory realm

User concepts

Access control

Depending on the underlying data source

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes

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More resources

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1 April 2015, Paul Andlinger

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2 March 2016, Paul Andlinger

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Recent citations in the news

Apache Drill vs. Apache Spark — Which SQL query engine is better for you?
23 September 2019, Towards Data Science

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

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

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24 October 2022, The Daily Swig

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14 November 2022, TheServerSide.com

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9 June 2020, diginomica

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10 June 2020, AiThority

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12 September 2017, Solutions Review

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27 February 2021, DataDrivenInvestor

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