Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Yes
API Access
Has API
No
Integrations
3forge
No
Advanced Query Tool (AQT)
No
Amazon Web Services (AWS)
No
Datametica
No
Digna
No
Greenhouse
Yes
HubSpot CRM
Yes
IBM Cognos Analytics
No
IBM watsonx.data
No
IRI Voracity
No
Integrations
3forge
Yes
Advanced Query Tool (AQT)
Yes
Amazon Web Services (AWS)
Yes
Datametica
Yes
Digna
Yes
Greenhouse
No
HubSpot CRM
No
IBM Cognos Analytics
Yes
IBM watsonx.data
Yes
IRI Voracity
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
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
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No