DBMS > Badger vs. Netezza vs. OushuDB

System Properties Comparison Badger vs. Netezza vs. OushuDB

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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.

Data warehouse and analytics appliance part of IBM PureSystems

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Key-value store

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

github.com/dgraph-io/badger

www.ibm.com/products/netezza

www.oushu.com/product/oushuDB

Technical documentation

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

www.oushu.com/documentation

Developer

DGraph Labs

IBM

Oushu

Initial release

2017

2000

Current release

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

included in appliance

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

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

In-memory capabilities

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

User concepts

Access control

Users with fine-grained authorization concept

Kerberos, SSL and role based access

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