DBMS > AlaSQL vs. GBase vs. Google BigQuery vs. Microsoft Azure AI Search

System Properties Comparison AlaSQL vs. GBase vs. Google BigQuery vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Large scale data warehouse service with append-only tables

Search-as-a-service for web and mobile app development

Primary database model

Document store
Relational DBMS

Relational DBMS

Search engine

Secondary database models

Vector 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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Website

alasql.org

www.gbase.cn

cloud.google.com/bigquery

azure.microsoft.com/en-us/services/search

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

learn.microsoft.com/en-us/azure/search

Developer

Andrey Gershun & Mathias R. Wulff

General Data Technology Co., Ltd.

Google

Microsoft

Initial release

2014

2004

2010

2015

Current release

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

MIT-License

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, Java, Python

Server operating systems

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

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

Standard with numerous extensions

yes

APIs and other access methods

JavaScript API

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

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

Google Cloud Identity & Access Management (IAM)

yes

using Azure authentication

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