DBMS > BaseX vs. FatDB vs. Google Cloud Firestore vs. Linter vs. Lovefield

System Properties Comparison BaseX vs. FatDB vs. Google Cloud Firestore vs. Linter vs. Lovefield

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

RDBMS for high security requirements

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Native XML DBMS

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

basex.org

firebase.google.com/products/firestore

linter.ru

google.github.io/lovefield

Technical documentation

docs.basex.org

firebase.google.com/docs/firestore

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

Developer

BaseX GmbH

FatCloud

Google

relex.ru

Google

Initial release

2007

2012

2017

1990

2014

Current release

10.7, August 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

Apache 2.0

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

C and C++

JavaScript

Server operating systems

Linux
OS X
Windows

Windows

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

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

Via inetgration in SQL Server

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

via events

yes

via applications

yes, with Cloud Functions

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate 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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Can implement custom security layer via applications

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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