DBMS > Apache Drill vs. Apache Druid vs. Lovefield vs. mSQL vs. SQLite

System Properties Comparison Apache Drill vs. Apache Druid vs. Lovefield vs. mSQL vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

drill.apache.org

druid.apache.org

google.github.io/lovefield

hughestech.com.au/products/msql

www.sqlite.org

Technical documentation

drill.apache.org/docs

druid.apache.org/docs/latest/design

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

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Apache Software Foundation and contributors

Google

Hughes Technologies

Dwayne Richard Hipp

Initial release

2012

2014

1994

2000

Current release

1.20.3, January 2023

29.0.1, April 2024

2.1.12, February 2017

4.4, October 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache license v2

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

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

server-less

Data scheme

schema-free

yes

schema-less columns are supported

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL for querying

SQL-like query language

via JavaScript builder pattern

A subset of ANSI SQL is implemented

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

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

User concepts

Access control

Depending on the underlying data source

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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