DBMS > BaseX vs. FatDB vs. Sqrrl

System Properties Comparison BaseX vs. FatDB vs. Sqrrl

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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.

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines 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.

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Native XML DBMS

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Website

basex.org

sqrrl.com

Technical documentation

docs.basex.org

Developer

BaseX GmbH

FatCloud

Amazon

originally Sqrrl Data, Inc.

Initial release

2007

2012

Current release

10.7, August 2023

License

Commercial or Open Source

Open Source

BSD license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

XQuery supports types

yes

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

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

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via events

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Can implement custom security layer via applications

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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