DBMS > Brytlyt vs. FatDB vs. LevelDB vs. RDF4J

System Properties Comparison Brytlyt vs. FatDB vs. LevelDB vs. RDF4J

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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.

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

RDF store

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

brytlyt.io

github.com/google/leveldb

rdf4j.org

Technical documentation

docs.brytlyt.io

github.com/google/leveldb/blob/main/doc/index.md

rdf4j.org/documentation

Developer

Brytlyt

FatCloud

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2012

2011

2004

Current release

5.0, August 2023

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and CUDA

C++

Java

Server operating systems

Linux
OS X
Windows

Windows

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

via applications

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory storage is supported as well

User concepts

Access control

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

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More resources

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