Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon Redshift is a modern cloud data warehouse platform developed by AWS to help organizations run large-scale analytics and AI-powered workloads with exceptional speed, scalability, and cost efficiency. The solution enables businesses to unify data across Amazon S3 data lakes, Redshift data warehouses, and federated third-party data sources using a secure and open lakehouse architecture. Redshift supports SQL-based analytics and provides organizations with the ability to process massive volumes of data while maintaining strong price-performance advantages compared to traditional cloud data warehouse platforms. The platform features AWS Graviton-powered RG instances that deliver faster query performance and lower operational costs while supporting open data formats such as Apache Iceberg and Apache Parquet. Redshift Serverless allows users to run analytics without provisioning or managing infrastructure, making it easier for teams to scale resources dynamically based on workload demands. The solution also includes zero-ETL integrations that enable near real-time analytics by connecting operational databases, streaming systems, and enterprise applications without requiring complex data engineering workflows. Amazon Redshift integrates with Amazon SageMaker for unified analytics and machine learning capabilities while also supporting Amazon Bedrock for generative AI applications and structured knowledge management. Organizations across industries use Redshift to improve forecasting, optimize business intelligence, accelerate machine learning operations, and monetize data assets more effectively.
Description
biGENIUS automates all phases of analytic data management solutions (e.g. data warehouses, data lakes and data marts. thereby allowing you to turn your data into a business as quickly and cost-effectively as possible. Your data analytics solutions will save you time, effort and money. Easy integration of new ideas and data into data analytics solutions. The metadata-driven approach allows you to take advantage of new technologies. Advancement of digitalization requires traditional data warehouses (DWH) as well as business intelligence systems to harness an increasing amount of data. Analytical data management is essential to support business decision making today. It must integrate new data sources, support new technologies, and deliver effective solutions faster than ever, ideally with limited resources.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amundsen
Yes
Anomalo
Yes
Codd AI
Yes
Composable DataOps Platform
Yes
Datazoom
Yes
Emgage
Yes
IBM Cognos Analytics
Yes
Informatica Intelligent Cloud Services
Yes
Latitude
Yes
Logstash
Yes
Integrations
Amundsen
No
Anomalo
No
Codd AI
No
Composable DataOps Platform
No
Datazoom
No
Emgage
No
IBM Cognos Analytics
No
Informatica Intelligent Cloud Services
No
Latitude
No
Logstash
No
Pricing Details
$0.543 per hour
Free Trial
Yes
Free Version
No
Pricing Details
833CHF/seat/month
Essential, Professional, and Enterprise subscription plans available
Non-Commercial license: free for personal use
Non-Commercial license: free for personal use
Free Trial
Yes
Free Version
Yes
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
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)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/redshift/
Vendor Details
Company Name
biGENIUS AG
Founded
2011
Country
Switzerland
Website
www.bigenius-x.com
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 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
No
Data Cleansing
Yes
Data Mining
No
Data Visualization
No
Data Warehousing
Yes
High Volume Processing
No
No-Code Sandbox
Yes
Predictive Analytics
No
Templates
Yes
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
Yes
Data Quality Control
Yes
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No