DBMS > Apache Kylin vs. BaseX vs. DuckDB vs. Faircom DB vs. Firebase Realtime Database

System Properties Comparison Apache Kylin vs. BaseX vs. DuckDB vs. Faircom DB vs. Firebase Realtime Database

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Primary database model

Relational DBMS

Native XML DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Website

kylin.apache.org

basex.org

duckdb.org

www.faircom.com/products/faircom-db

firebase.google.com/products/realtime-database

Technical documentation

kylin.apache.org/docs

docs.basex.org

duckdb.org/docs

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

firebase.google.com/docs/database

Developer

Apache Software Foundation, originally contributed from eBay Inc

BaseX GmbH

FairCom Corporation

Google

acquired by Google 2014

Initial release

2015

2007

2018

1979

2012

Current release

3.1.0, July 2020

10.7, August 2023

0.10, February 2024

V12, November 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD license

Open Source

MIT License

commercial

Restricted, free version available

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

C++

ANSI C, C++

Server operating systems

Linux

Linux
OS X
Windows

server-less

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

Data scheme

yes

schema-free

yes

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

ANSI SQL for queries (using Apache Calcite)

yes

yes, ANSI SQL with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Android
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

Triggers

yes

via events

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

tunable from ACID to Eventually Consistent

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Fine grained access rights according to SQL-standard with additional protections for files

yes, based on authentication and database rules

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More resources

DB-Engines blog posts

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