DBMS > Amazon Redshift vs. Brytlyt vs. eXtremeDB vs. Microsoft SQL Server vs. OpenEdge

System Properties Comparison Amazon Redshift vs. Brytlyt vs. eXtremeDB vs. Microsoft SQL Server vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

aws.amazon.com/redshift

brytlyt.io

www.mcobject.com

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

www.progress.com/openedge

Technical documentation

docs.aws.amazon.com/redshift

docs.brytlyt.io

www.mcobject.com/docs/extremedb.htm

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

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon (based on PostgreSQL)

Brytlyt

McObject

Microsoft

Progress Software Corporation

Initial release

2012

2016

2001

1989

1984

Current release

5.0, August 2023

8.2, 2021

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

C and C++

C++

Server operating systems

hosted

Linux
OS X
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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.

support of XML interfaces available

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with the option: eXtremeSQL

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC

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

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C#
C++
Java
Lua
Python
Scala

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

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

in PL/pgSQL

yes

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

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

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

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Users and groups

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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