DBMS > Brytlyt vs. FatDB

System Properties Comparison Brytlyt vs. FatDB

Please select another system to include it in the comparison.

Our visitors often compare Brytlyt and FatDB with DuckDB.

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.

Primary database model

Relational DBMS

Document store
Key-value store

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

Score	0.27
Rank	#289	Overall
	#131	Relational DBMS

Website

brytlyt.io

Technical documentation

docs.brytlyt.io

Developer

Brytlyt

FatCloud

Initial release

2016

2012

Current release

5.0, August 2023

License

Commercial or Open Source

commercial

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

Server operating systems

Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

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

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

The insideAI News IMPACT 50 List for Q2 2022
27 April 2022, insideBIGDATA

provided by Google News

Share this page