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DBMS > Apache Drill vs. Drizzle vs. Heroic vs. SQL.JS

System Properties Comparison Apache Drill vs. Drizzle vs. Heroic vs. SQL.JS

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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.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Port of SQLite to JavaScript

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.57
Rank	#248	Overall
	#114	Relational DBMS

Website

drill.apache.org

github.com/spotify/heroic

Technical documentation

drill.apache.org/docs

spotify.github.io/heroic

sql.js.org/documentation/index.html

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Spotify

Alon Zakai

enhancements implemented by others

Initial release

2012

2008

2014

2012

Current release

1.20.3, January 2023

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

no

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

JavaScript

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes

yes

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.

no

no

no

Secondary indexes

no

yes

yes

via Elasticsearch

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

with proprietary extensions

no

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JavaScript API

Supported programming languages

C++

C
C++
Java
PHP

JavaScript

Server-side scripts

Stored procedures

user defined functions

no

no

no

Triggers

no

no

hooks for callbacks inside the server can be used.

no

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

no

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

no

yes

no

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

no

ACID

no

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

yes

no

except by serializing a db to a file

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

no

yes

User concepts

Access control

Depending on the underlying data source

Pluggable authentication mechanisms

e.g. LDAP, HTTP

no

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More resources

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