DBMS > Brytlyt vs. CouchDB vs. Greenplum vs. Microsoft SQL Server

System Properties Comparison Brytlyt vs. CouchDB vs. Greenplum vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

brytlyt.io

couchdb.apache.org

greenplum.org

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

Technical documentation

docs.brytlyt.io

docs.couchdb.org/en/stable

docs.greenplum.org

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

Developer

Brytlyt

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Pivotal Software Inc.

Microsoft

Initial release

2016

2005

1989

Current release

5.0, August 2023

3.3.3, December 2023

7.0.0, September 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C, C++ and CUDA

Erlang

C++

Server operating systems

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Linux

Linux
Windows

Data scheme

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

since Version 4.2

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC

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

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C
Java
Perl
Python
R

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

View functions in JavaScript

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

yes, but depending on the SQL-Server Edition

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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