DBMS > AlaSQL vs. Apache Drill vs. Google BigQuery vs. JaguarDB vs. Lovefield

System Properties Comparison AlaSQL vs. Apache Drill vs. Google BigQuery vs. JaguarDB vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Large scale data warehouse service with append-only tables

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Vector DBMS

Relational 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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

alasql.org

drill.apache.org

cloud.google.com/bigquery

www.jaguardb.com

google.github.io/lovefield

Technical documentation

github.com/AlaSQL/alasql

drill.apache.org/docs

cloud.google.com/bigquery/docs

www.jaguardb.com/support.html

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Google

DataJaguar, Inc.

Google

Initial release

2014

2012

2010

2015

2014

Current release

1.20.3, January 2023

3.3 July 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

commercial

Open Source

GPL V3.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

the server part. Clients available in other languages

JavaScript

Server operating systems

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

Linux
OS X
Windows

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JavaScript API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

JavaScript

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

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

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

Since BigQuery is designed for querying data

ACID

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

User concepts

Access control

Depending on the underlying data source

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

Google Cloud Identity & Access Management (IAM)

rights management via user accounts

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