DBMS > Brytlyt vs. FatDB vs. Microsoft SQL Server vs. PouchDB vs. SAP Adaptive Server

System Properties Comparison Brytlyt vs. FatDB vs. Microsoft SQL Server vs. PouchDB vs. SAP Adaptive Server

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.

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

brytlyt.io

www.microsoft.com/en-us/sql-server

pouchdb.com

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

docs.brytlyt.io

learn.microsoft.com/en-US/sql/sql-server

pouchdb.com/guides

help.sap.com/docs/SAP_ASE

Developer

Brytlyt

FatCloud

Microsoft

Apache Software Foundation

SAP, Sybase

Initial release

2016

2012

1989

2012

1987

Current release

5.0, August 2023

SQL Server 2022, November 2022

7.1.1, June 2019

16.0

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

C++

JavaScript

C and C++

Server operating systems

Linux
OS X
Windows

Windows

Linux
Windows

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

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

yes

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

via applications

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

View functions in JavaScript

Java and Transact-SQL

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication
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

Eventual Consistency
Immediate Consistency

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

by using IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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