DBMS > AlaSQL vs. Amazon DocumentDB vs. Apache Drill vs. Google BigQuery

System Properties Comparison AlaSQL vs. Amazon DocumentDB vs. Apache Drill vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Large scale data warehouse service with append-only tables

Primary database model

Document store
Relational DBMS

Document store

Document store
Relational DBMS

Relational DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	1.89
Rank	#137	Overall
	#24	Document stores

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Website

alasql.org

aws.amazon.com/documentdb

drill.apache.org

cloud.google.com/bigquery

Technical documentation

github.com/AlaSQL/alasql

aws.amazon.com/documentdb/resources

drill.apache.org/docs

cloud.google.com/bigquery/docs

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Google

Initial release

2014

2019

2012

2010

Current release

1.20.3, January 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2

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

Server operating systems

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

hosted

Linux
OS X
Windows

hosted

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

APIs and other access methods

JavaScript API

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

JavaScript

Go
Java
JavaScript (Node.js)
PHP
Python

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

yes

only for local storage and DOM-storage

Atomic single-document operations

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

yes

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

Access rights for users and roles

Depending on the underlying data source

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

Google Cloud Identity & Access Management (IAM)

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