DBMS > AlaSQL vs. Apache Drill vs. DataFS vs. Drizzle vs. Google BigQuery

System Properties Comparison AlaSQL vs. Apache Drill vs. DataFS vs. Drizzle vs. Google BigQuery

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Large scale data warehouse service with append-only tables

Primary database model

Document store
Relational DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

alasql.org

drill.apache.org

newdatabase.com

cloud.google.com/bigquery

Technical documentation

github.com/AlaSQL/alasql

drill.apache.org/docs

dev.mobiland.com/Overview.xsp

cloud.google.com/bigquery/docs

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Mobiland AG

Drizzle project, originally started by Brian Aker

Google

Initial release

2014

2012

2018

2008

2010

Current release

1.20.3, January 2023

1.1.263, October 2022

7.2.4, September 2012

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

commercial

Open Source

GNU GPL

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

Server operating systems

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

Linux
OS X
Windows

Windows

FreeBSD
Linux
OS X

hosted

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

.NET Client API
Proprietary client DLL
WinRT client

JDBC

RESTful HTTP/JSON API

Supported programming languages

JavaScript

C++

.Net
C
C#
C++
VB.Net

C
C++
Java
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

no, except callback-events from server when changes happened

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

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

yes

only for local storage and DOM-storage

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Depending on the underlying data source

Windows-Profile

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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