+
+

Related Products

  • Teradata VantageCloud
    992 Ratings
    Visit Website
  • AnalyticsCreator
    46 Ratings
    Visit Website
  • Google Cloud BigQuery
    1,927 Ratings
    Visit Website
  • Globalscape Enhanced File Transfer (EFT)
    85 Ratings
    Visit Website
  • Google Cloud SQL
    539 Ratings
    Visit Website
  • Fax.Cloud
    1 Rating
    Visit Website
  • Kamatera
    152 Ratings
    Visit Website
  • Comet Backup
    215 Ratings
    Visit Website
  • Windocks
    7 Ratings
    Visit Website
  • PeerGFS
    23 Ratings
    Visit Website

About

100% compatible with Netezza. Single command-line upgrade path. Available on premises, on cloud or hybrid. IBM® Netezza® Performance Server for IBM Cloud Pak® for Data is an advanced data warehouse and analytics platform available both on premises and on cloud. With enhancements to in-database analytics capabilities, this next generation of Netezza enables you to do data science and machine learning with data volumes scaling into the petabytes. Failure detection and fast failure recovery. Single command-line upgrade to existing systems. Ability to query many systems as one. Choose the data center or availability zone closest to you, set the number of compute units and amount of storage required to run, and go. IBM® Netezza® Performance Server for IBM Cloud Pak® for Data is available on IBM Cloud®, Amazon Web Services (AWS) and Microsoft Azure. Deployable on a private cloud, Netezza is powered by IBM Cloud Pak for Data System.

About

The Stackable data platform was designed with openness and flexibility in mind. It provides you with a curated selection of the best open source data apps like Apache Kafka, Apache Druid, Trino, and Apache Spark. While other current offerings either push their proprietary solutions or deepen vendor lock-in, Stackable takes a different approach. All data apps work together seamlessly and can be added or removed in no time. Based on Kubernetes, it runs everywhere, on-prem or in the cloud. stackablectl and a Kubernetes cluster are all you need to run your first stackable data platform. Within minutes, you will be ready to start working with your data. Configure your one-line startup command right here. Similar to kubectl, stackablectl is designed to easily interface with the Stackable Data Platform. Use the command line utility to deploy and manage stackable data apps on Kubernetes. With stackablectl, you can create, delete, and update components.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies and analysts that require a data warehouse and analytics platform to do data science and machine learning with data volumes

Audience

Enterprises wanting a solution to deploy and run their data platforms on their sovereign Kubernetes.

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

IBM
Founded: 1911
United States
www.ibm.com/products/netezza

Company Information

Stackable
Founded: 2020
Germany
stackable.tech/

Alternatives

Alternatives

E-MapReduce

E-MapReduce

Alibaba
Canvas Credentials

Canvas Credentials

Instructure
BigLake

BigLake

Google

Categories

Categories

Data Warehouse Features

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Data Management Features

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Integrations

Amazon S3
Amazon Web Services (AWS)
Apache Spark
Apache ZooKeeper
Captain Compliance
Datametica
DbVisualizer
IBM Cloud Pak for Data
IBM Cognos Analytics
IRI Voracity
Impetus
MinIO
Nucleon Database Master
RazorSQL
SAS Federation Server
SOLIXCloud
StreamFlux
Trino

Integrations

Amazon S3
Amazon Web Services (AWS)
Apache Spark
Apache ZooKeeper
Captain Compliance
Datametica
DbVisualizer
IBM Cloud Pak for Data
IBM Cognos Analytics
IRI Voracity
Impetus
MinIO
Nucleon Database Master
RazorSQL
SAS Federation Server
SOLIXCloud
StreamFlux
Trino
Claim IBM Netezza Performance Server and update features and information
Claim IBM Netezza Performance Server and update features and information
Claim Stackable and update features and information
Claim Stackable and update features and information