Average Ratings 0 Ratings
Average Ratings 0 Ratings
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.
Description
Talend Data Fabric's cloud services are able to efficiently solve all your integration and integrity problems -- on-premises or in cloud, from any source, at any endpoint. Trusted data delivered at the right time for every user. With an intuitive interface and minimal coding, you can easily and quickly integrate data, files, applications, events, and APIs from any source to any location. Integrate quality into data management to ensure compliance with all regulations. This is possible through a collaborative, pervasive, and cohesive approach towards data governance. High quality, reliable data is essential to make informed decisions. It must be derived from real-time and batch processing, and enhanced with market-leading data enrichment and cleaning tools. Make your data more valuable by making it accessible internally and externally. Building APIs is easy with the extensive self-service capabilities. This will improve customer engagement.
API Access
Has API
No
API Access
Has API
No
Integrations
Adobe Marketo Engage
No
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
DBHawk
Yes
Datametica
Yes
DbVisualizer
Yes
Delta Lake
No
Digna
Yes
Google Cloud Platform
No
IBM Cloud Pak for Data
Yes
Integrations
Adobe Marketo Engage
Yes
Amazon S3
No
Amazon Web Services (AWS)
No
DBHawk
No
Datametica
No
DbVisualizer
No
Delta Lake
Yes
Digna
No
Google Cloud Platform
Yes
IBM Cloud Pak for Data
No
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
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/netezza
Vendor Details
Company Name
Qlik
Founded
1993
Country
United States
Website
www.talend.com
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
Product Features
Big Data
Collaboration
Yes
Data Blends
Yes
Data Cleansing
Yes
Data Mining
Yes
Data Visualization
Yes
Data Warehousing
Yes
High Volume Processing
Yes
No-Code Sandbox
Yes
Predictive Analytics
Yes
Templates
Yes
Data Cleansing
Address/ZIP Code Cleaning
Yes
Charting
Yes
Data Consolidation / ETL
Yes
Data Mapping
Yes
Multi Data Format Support
Yes
Phone/Email Validation
No
Raw Data Ingestion
Yes
Sample Testing
Yes
Validation / Matching / Reconciliation
Yes
Data Extraction
Disparate Data Collection
Yes
Document Extraction
Yes
Email Address Extraction
Yes
IP Address Extraction
Yes
Image Extraction
Yes
Phone Number Extraction
Yes
Pricing Extraction
Yes
Web Data Extraction
Yes
Data Fabric
Data Access Management
No
Data Analytics
No
Data Collaboration
No
Data Lineage Tools
No
Data Networking / Connecting
No
Metadata Functionality
No
No Data Redundancy
No
Persistent Data Management
No
Data Governance
Access Control
Yes
Data Discovery
Yes
Data Mapping
Yes
Data Profiling
Yes
Deletion Management
Yes
Email Management
Yes
Policy Management
Yes
Process Management
Yes
Roles Management
Yes
Storage Management
Yes
Data Management
Customer Data
Yes
Data Analysis
Yes
Data Capture
Yes
Data Integration
Yes
Data Migration
Yes
Data Quality Control
Yes
Data Security
Yes
Information Governance
Yes
Master Data Management
Yes
Match & Merge
Yes
Data Quality
Address Validation
Yes
Data Deduplication
Yes
Data Discovery
Yes
Data Profililng
Yes
Master Data Management
Yes
Match & Merge
Yes
Metadata Management
Yes
Data Warehouse
Ad hoc Query
No
Analytics
Yes
Data Integration
Yes
Data Migration
Yes
Data Quality Control
Yes
ETL - Extract / Transfer / Load
Yes
In-Memory Processing
No
Match & Merge
Yes
Enterprise Service Bus (ESB)
Data Source Connectors
No
Electronic Data Interchange (EDI)
No
Enterprise Application Integration
No
Enterprise Integration Patterns (EIP)
No
Integrations Management
No
Messaging
No
ETL
Data Analysis
Yes
Data Filtering
No
Data Quality Control
Yes
Job Scheduling
No
Match & Merge
Yes
Metadata Management
Yes
Non-Relational Transformations
No
Version Control
No
Integration
Dashboard
Yes
ETL - Extract / Transform / Load
Yes
Metadata Management
Yes
Multiple Data Sources
Yes
Web Services
Yes
Master Data Management
Data Governance
Yes
Data Masking
Yes
Data Source Integrations
Yes
Hierarchy Management
Yes
Match & Merge
Yes
Metadata Management
Yes
Multi-Domain
No
Process Management
No
Relationship Mapping
No
Visualization
Yes