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Description
Consolidate all your information into a single platform featuring over 100 built-in and universal API data connectors, ensuring easy access for your entire team. Effortlessly manipulate your data with just a few clicks, and create powerful data pipelines using integrated data processing tools and automated scheduling features. By streamlining the manual transfer of data, you can reclaim valuable hours that would otherwise be spent on this tedious task. Leverage Workflow to automate transitions between databases and BI tools, as well as from applications back to databases. A comprehensive array of data cleaning and transformation utilities is provided in a no-code environment, removing the necessity for complex expressions or programming. Remember, data becomes valuable only when actionable insights are extracted from it. Elevate your database into a sophisticated analytical engine equipped with native cloud-based BI tools. There’s no need for additional connectors, as all data projects on Acho can be swiftly analyzed and visualized using our Visual Panel right out of the box, ensuring rapid results. Additionally, this approach enhances collaborative efforts by allowing team members to engage with data insights collectively.
Description
Fully compatible with Netezza, this solution offers a streamlined command-line upgrade option. It can be deployed on-premises, in the cloud, or through a hybrid model. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as a sophisticated platform for data warehousing and analytics, catering to both on-premises and cloud environments. With significant improvements in in-database analytics functions, this next-generation Netezza empowers users to engage in data science and machine learning with datasets that can reach petabyte levels. It includes features for detecting failures and ensuring rapid recovery, making it robust for enterprise use. Users can upgrade existing systems using a single command-line interface. The platform allows for querying multiple systems as a cohesive unit. You can select the nearest data center or availability zone, specify the desired compute units and storage capacity, and initiate the setup seamlessly. Furthermore, the IBM® Netezza® Performance Server is accessible on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be implemented on a private cloud, all powered by the capabilities of IBM Cloud Pak for Data System. This flexibility enables organizations to tailor the deployment to their specific needs and infrastructure.
API Access
Has API
API Access
Has API
Integrations
Advanced Query Tool (AQT)
Amazon S3
Greenhouse
HubSpot CRM
HubSpot Customer Platform
IBM Cloud
IBM Cloud Pak for Data
IBM Cognos Analytics
IRI Voracity
Immuta
Integrations
Advanced Query Tool (AQT)
Amazon S3
Greenhouse
HubSpot CRM
HubSpot Customer Platform
IBM Cloud
IBM Cloud Pak for Data
IBM Cognos Analytics
IRI Voracity
Immuta
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Acho
Founded
2020
Country
United States
Website
acho.io
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/netezza
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
