DBMS > Apache Druid vs. BaseX vs. PouchDB vs. Quasardb vs. Snowflake

System Properties Comparison Apache Druid vs. BaseX vs. PouchDB vs. Quasardb vs. Snowflake

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

JavaScript DBMS with an API inspired by CouchDB

Distributed, high-performance timeseries database

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS
Time Series 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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

docs.basex.org

pouchdb.com/guides

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

BaseX GmbH

Apache Software Foundation

quasardb

Snowflake Computing Inc.

Initial release

2012

2007

2012

2009

2014

Current release

29.0.1, April 2024

10.7, August 2023

7.1.1, June 2019

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD license

Open Source

commercial

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

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

Java

JavaScript

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

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

BSD
Linux
OS X
Windows

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

integer and binary

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

via views

yes

with tags

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

JavaScript

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

user defined functions

Triggers

yes

via events

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

User concepts

Access control

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

Users with fine-grained authorization concept on 4 levels

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.