DBMS > Apache Drill vs. Google BigQuery vs. Lovefield vs. mSQL

System Properties Comparison Apache Drill vs. Google BigQuery vs. Lovefield vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

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Trend Chart

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Website

drill.apache.org

cloud.google.com/bigquery

google.github.io/lovefield

hughestech.com.au/products/msql

Technical documentation

drill.apache.org/docs

cloud.google.com/bigquery/docs

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

Developer

Apache Software Foundation

Google

Hughes Technologies

Initial release

2012

2010

2014

1994

Current release

1.20.3, January 2023

2.1.12, February 2017

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

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

Server operating systems

Linux
OS X
Windows

hosted

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

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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

SQL SELECT statement is SQL:2003 compliant

yes

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

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

yes

In-memory capabilities

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

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)

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