DBMS > Bangdb vs. Infobright vs. Linter vs. Microsoft SQL Server vs. OpenEdge

System Properties Comparison Bangdb vs. Infobright vs. Linter vs. Microsoft SQL Server vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

RDBMS for high security requirements

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

bangdb.com

ignitetech.com/softwarelibrary/infobrightdb

linter.ru

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

www.progress.com/openedge

Technical documentation

docs.bangdb.com

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

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Sachin Sinha, BangDB

Ignite Technologies Inc.; formerly InfoBright Inc.

relex.ru

Microsoft

Progress Software Corporation

Initial release

2012

2005

1990

1989

1984

Current release

BangDB 2.0, October 2021

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

BSD 3

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++

C and C++

C++

Server operating systems

Linux

Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL like support with command line tool

yes

close to SQL 92

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

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

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

yes

proprietary syntax with the possibility to convert from PL/SQL

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

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

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

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

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

Tunable consistency, set CAP knob accordingly

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

Users and groups

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