DBMS > Badger vs. Netezza vs. SpaceTime vs. Transwarp KunDB

System Properties Comparison Badger vs. Netezza vs. SpaceTime vs. Transwarp KunDB

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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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Secondary database models

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	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

github.com/dgraph-io/badger

www.ibm.com/products/netezza

www.mireo.com/spacetime

www.transwarp.cn/en/product/kundb

Technical documentation

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

Developer

DGraph Labs

IBM

Mireo

Transwarp

Initial release

2017

2000

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

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

A subset of ANSI SQL is implemented

yes

APIs and other access methods

JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

C#
C++
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Fixed-grid hypercubes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

yes

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More resources

Recent citations in the news

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

Netezza Performance Server
12 August 2020, IBM

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News

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