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Description
Datonix reduces the need for data movement, provides built-in compliance features, and enables real-time data operations, which is crucial since transferring data to a server, such as a data warehouse, can create significant delays and incur high costs. Utilizing the GRID architecture, Datonix processes data without requiring it to be moved, thereby eliminating these barriers. In the current landscape, organizations often face the challenge of making large investments and enduring lengthy maintenance efforts to update their data management systems. Datonix effectively addresses all critical functions needed to modernize a database or archive. Traditional data management solutions focused on real-time analytics often demand intricate data operations and substantial processing power. However, the algorithms employed by Datonix significantly reduce the reliance on extensive processing resources while streamlining data operations, leading to enhanced efficiency and cost-effectiveness in data management.
Description
Boost the pace of AI innovation through cloud-native data integration offered by IBM Cloud Pak for Data. With AI-driven data integration capabilities accessible from anywhere, the effectiveness of your AI and analytics is directly linked to the quality of the data supporting them. Utilizing a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data ensures the delivery of superior data. This solution merges top-tier data integration with DataOps, governance, and analytics within a unified data and AI platform. By automating administrative tasks, it helps in lowering total cost of ownership (TCO). The platform's AI-based design accelerators, along with ready-to-use integrations with DataOps and data science services, significantly hasten AI advancements. Furthermore, its parallelism and multicloud integration capabilities enable the delivery of reliable data on a large scale across diverse hybrid or multicloud settings. Additionally, you can efficiently manage the entire data and analytics lifecycle on the IBM Cloud Pak for Data platform, which encompasses a variety of services such as data science, event messaging, data virtualization, and data warehousing, all bolstered by a parallel engine and automated load balancing features. This comprehensive approach ensures that your organization stays ahead in the rapidly evolving landscape of data and AI.
API Access
Has API
No
API Access
Has API
No
Integrations
ActiveBatch Workload Automation
No
Control-M
No
FairCom DB
No
FairCom EDGE
No
IBM Cloud Pak for Applications
No
IBM Watson Studio
No
IRI FieldShield
No
MettleCI
No
Origina
No
Pantomath
No
Integrations
ActiveBatch Workload Automation
Yes
Control-M
Yes
FairCom DB
Yes
FairCom EDGE
Yes
IBM Cloud Pak for Applications
Yes
IBM Watson Studio
Yes
IRI FieldShield
Yes
MettleCI
Yes
Origina
Yes
Pantomath
Yes
Pricing Details
No price information available.
Free Trial
No
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
Yes
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
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Datonix
Founded
2015
Country
Italy
Website
www.datonix.it/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/infosphere-datastage
Product Features
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Data Lineage
Database Change Impact Analysis
No
Filter Lineage Links
No
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
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
