DBMS > BaseX vs. Databricks vs. Faircom EDGE vs. RethinkDB

System Properties Comparison BaseX vs. Databricks vs. Faircom EDGE vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Native XML DBMS

Document store
Relational DBMS

Key-value store
Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

basex.org

www.databricks.com

www.faircom.com/products/faircom-edge

rethinkdb.com

Technical documentation

docs.basex.org

docs.databricks.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

rethinkdb.com/docs

Developer

BaseX GmbH

Databricks

FairCom Corporation

The Linux Foundation

since July 2017

Initial release

2007

2013

1979

2009

Current release

11.0, June 2024

V3, October 2020

2.4.1, August 2020

License

Commercial or Open Source

Open Source

BSD license

commercial

Restricted, free version available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

ANSI C, C++

C++

Server operating systems

Linux
OS X
Windows

hosted

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

XQuery supports types

yes, ANSI Standard SQL Types

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

with Databricks SQL

yes

ANSI SQL queries

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC
ODBC
RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Python
R
Scala

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

yes

.Net, JavaScript, C/C++

Triggers

yes

via events

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

multiple readers, single writer

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

MVCC based

Durability

Support for making data persistent

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes

users and table-level permissions

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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