DBMS > Apache Drill vs. Drizzle vs. H2 vs. Heroic vs. PouchDB

System Properties Comparison Apache Drill vs. Drizzle vs. H2 vs. Heroic vs. PouchDB

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

drill.apache.org

www.h2database.com

github.com/spotify/heroic

pouchdb.com

Technical documentation

drill.apache.org/docs

www.h2database.com/html/main.html

spotify.github.io/heroic

pouchdb.com/guides

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Thomas Mueller

Spotify

Apache Software Foundation

Initial release

2012

2008

2005

2014

2012

Current release

1.20.3, January 2023

7.2.4, September 2012

2.2.220, July 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

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

JavaScript

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

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

Data scheme

schema-free

yes

schema-free

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

via Elasticsearch

yes

via views

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

JDBC
ODBC

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

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C++

C
C++
Java
PHP

Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

View functions in JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual 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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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

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More resources

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Recent citations in the news

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