DBMS > Netezza vs. OpenTSDB vs. XTDB vs. Yanza

System Properties Comparison Netezza vs. OpenTSDB vs. XTDB vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Data warehouse and analytics appliance part of IBM PureSystems

Scalable Time Series DBMS based on HBase

A general purpose database with bitemporal SQL and Datalog and graph queries

Time Series DBMS for IoT Applications

Primary database model

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

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.ibm.com/products/netezza

opentsdb.net

github.com/xtdb/xtdb
www.xtdb.com

yanza.com

Technical documentation

opentsdb.net/docs/build/html/index.html

www.xtdb.com/docs

Developer

IBM

currently maintained by Yahoo and other contributors

Juxt Ltd.

Yanza

Initial release

2000

2011

2019

2015

Current release

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

LGPL

Open Source

MIT License

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Clojure

Server operating systems

Linux

included in appliance

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
OLE DB

HTTP API
Telnet API

HTTP REST
JDBC

HTTP API

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

Erlang
Go
Java
Python
R
Ruby

Clojure
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on HBase

yes, each node contains all data

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Immediate Consistency

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

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.com

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.com

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

A real-time processing revival - O'Reilly Radar
2 April 2015, O'Reilly Radar

provided by Google News

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