DBMS > Badger vs. Bangdb vs. Netezza vs. OpenEdge

System Properties Comparison Badger vs. Bangdb vs. Netezza vs. OpenEdge

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Data warehouse and analytics appliance part of IBM PureSystems

Application development environment with integrated database management system

Primary database model

Key-value store

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

github.com/dgraph-io/badger

bangdb.com

www.ibm.com/products/netezza

www.progress.com/openedge

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.bangdb.com

documentation.progress.com/output/ua/OpenEdge_latest

Developer

DGraph Labs

Sachin Sinha, BangDB

IBM

Progress Software Corporation

Initial release

2017

2012

2000

1984

Current release

BangDB 2.0, October 2021

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD 3

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

included in appliance

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

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

JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

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

User concepts

Access control

yes (enterprise version only)

Users with fine-grained authorization concept

Users and groups

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More resources

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