DBMS > Apache Druid vs. JaguarDB vs. Quasardb vs. Sequoiadb vs. SQLite

System Properties Comparison Apache Druid vs. JaguarDB vs. Quasardb vs. Sequoiadb vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Performant, highly scalable DBMS for AI and IoT applications

Distributed, high-performance timeseries database

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Key-value store
Vector DBMS

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

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

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

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

www.jaguardb.com/support.html

doc.quasar.ai/master

www.sequoiadb.com/en/index.php?m=Files&a=index

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

DataJaguar, Inc.

quasardb

Sequoiadb Ltd.

Dwayne Richard Hipp

Initial release

2012

2015

2009

2013

2000

Current release

29.0.1, April 2024

3.3 July 2023

3.14.1, January 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPL V3.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Server: AGPL; Client: Apache V2

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

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
OS X
Unix

Linux

BSD
Linux
OS X
Windows

Linux

server-less

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

integer and binary

yes

oid, date, timestamp, binary, regex

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

with tags

yes

SQL

Support of SQL

SQL for querying

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

HTTP API

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net
C++
Java
PHP
Python

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

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

Source-replica replication with selectable replication factor

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

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

rights management via user accounts

Cryptographically strong user authentication and audit trail

simple password-based access control

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