DBMS > AlaSQL vs. Apache Drill vs. Drizzle vs. H2 vs. SAP IQ

System Properties Comparison AlaSQL vs. Apache Drill vs. Drizzle vs. H2 vs. SAP IQ

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

JavaScript DBMS library

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.

Columnar RDBMS optimized for Big Data analytics

Primary database model

Document store
Relational DBMS

Relational DBMS

column-oriented

Secondary database models

Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

alasql.org

drill.apache.org

www.h2database.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

github.com/AlaSQL/alasql

drill.apache.org/docs

www.h2database.com/html/main.html

help.sap.com/docs/SAP_IQ

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Thomas Mueller

SAP, formerly Sybase

Initial release

2014

2012

2008

2005

1994

Current release

1.20.3, January 2023

7.2.4, September 2012

2.2.220, July 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

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

commercial

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

JavaScript

C++

Java

Server operating systems

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

Linux
OS X
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
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

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL SELECT statement is SQL:2003 compliant

yes

with proprietary extensions

yes

APIs and other access methods

JavaScript API

JDBC
ODBC
RESTful HTTP API

JDBC

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

JavaScript

C++

C
C++
Java
PHP

Java

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

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

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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.

yes

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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