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Description
DataLakeHouse.io Data Sync allows users to replicate and synchronize data from operational systems (on-premises and cloud-based SaaS), into destinations of their choice, primarily Cloud Data Warehouses. DLH.io is a tool for marketing teams, but also for any data team in any size organization. It enables business cases to build single source of truth data repositories such as dimensional warehouses, data vaults 2.0, and machine learning workloads.
Use cases include technical and functional examples, including: ELT and ETL, Data Warehouses, Pipelines, Analytics, AI & Machine Learning and Data, Marketing and Sales, Retail and FinTech, Restaurants, Manufacturing, Public Sector and more.
DataLakeHouse.io has a mission: to orchestrate the data of every organization, especially those who wish to become data-driven or continue their data-driven strategy journey. DataLakeHouse.io, aka DLH.io, allows hundreds of companies manage their cloud data warehousing solutions.
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
No
API Access
Has API
No
Integrations
Advanced Query Tool (AQT)
No
Aloha Cloud by NCR Voyix
Yes
Asana
Yes
Auth0
Yes
Calendly
Yes
HubSpot CRM
Yes
HubSpot Customer Platform
Yes
IRI Voracity
No
Lyftrondata
No
Microsoft 365
No
Integrations
Advanced Query Tool (AQT)
Yes
Aloha Cloud by NCR Voyix
No
Asana
No
Auth0
No
Calendly
No
HubSpot CRM
No
HubSpot Customer Platform
No
IRI Voracity
Yes
Lyftrondata
Yes
Microsoft 365
Yes
Pricing Details
$99
Free Trial
Yes
Free Version
Yes
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
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
DataLakeHouse.io
Founded
2019
Country
United States
Website
datalakehouse.io
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/netezza
Product Features
Data Management
Customer Data
Yes
Data Analysis
Yes
Data Capture
Yes
Data Integration
Yes
Data Migration
Yes
Data Quality Control
No
Data Security
Yes
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Replication
Asynchronous Data Replication
Yes
Automated Data Retention
Yes
Continuous Replication
Yes
Cross-Platform Replication
No
Dashboard
Yes
Instant Failover
No
Orchestration
Yes
Remote Database Replication
No
Reporting / Analytics
Yes
Simulation / Testing
No
Synchronous Data Replication
Yes
Data Warehouse
Ad hoc Query
Yes
Analytics
Yes
Data Integration
No
Data Migration
Yes
Data Quality Control
No
ETL - Extract / Transfer / Load
Yes
In-Memory Processing
No
Match & Merge
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