DBMS > Hawkular Metrics vs. LeanXcale vs. Netezza

System Properties Comparison Hawkular Metrics vs. LeanXcale vs. Netezza

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.01
Rank	#373	Overall
	#38	Time Series DBMS

Score	0.27
Rank	#288	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	7.34
Rank	#48	Overall
	#30	Relational DBMS

Website

www.hawkular.org

www.leanxcale.com

www.ibm.com/products/netezza

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Community supported by Red Hat

LeanXcale

IBM

Initial release

2014

2015

2000

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

Java

Server operating systems

Linux
OS X
Windows

Linux

included in appliance

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

through Apache Derby

yes

APIs and other access methods

HTTP REST

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
Python
Ruby

C
Java
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

yes

User concepts

Access control

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

RIP Netezza, IBM’s FPGA-powered data warehousing dream
3 July 2019, The Register

IBM Completes Acquisition of Netezza
26 October 2017, PR Newswire

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, businesswire.com

provided by Google News

Share this page