Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.
Description
Promethium empowers data and analytics teams to enhance their efficiency, enabling them to keep pace with the increasing volumes of data and the evolving demands of the business landscape. Merely linking to a data warehouse or lake for raw data access falls short of meeting the required standards. The process of refining datasets demands considerable effort from data teams, which are not expanding at the same rate as the influx of data or the appetite for insights. By leveraging Promethium, burdened data teams can optimize their workflows, leading to faster deliveries. The platform minimizes reliance on traditional ETL processes, granting on-demand access to data in its original location. This reduction in data movement not only conserves time but also cuts costs. With Promethium, an individual can achieve in mere minutes what generally requires a team several months and multiple tools to accomplish. Users can effortlessly connect and catalog data sources, as well as create and query cross-source datasets with just a few clicks, all without needing to write any code. This significant decrease in custom coding and ETL processes allows for real-time validation of data accuracy, eliminating the delays often associated with extensive ETL efforts. Additionally, the ability to instantly share completed work fosters a culture of reuse, preventing the need for repetitive recreation of analyses. Such features not only streamline operations but also enhance collaboration among team members.
API Access
Has API
No
API Access
Has API
No
Integrations
Looker
Yes
Microsoft Power BI
Yes
Tableau
Yes
AccessOwl
Yes
Apache Iceberg
Yes
BI Book
Yes
Cyral
Yes
DashboardFox
Yes
Emgage
Yes
HPE Ezmeral
Yes
Integrations
Looker
Yes
Microsoft Power BI
Yes
Tableau
Yes
AccessOwl
No
Apache Iceberg
No
BI Book
No
Cyral
No
DashboardFox
No
Emgage
No
HPE Ezmeral
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
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
No
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
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Dremio
Founded
2015
Country
United States
Website
www.dremio.com
Vendor Details
Company Name
Promethium
Founded
2018
Country
United States
Website
www.pm61data.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 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
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
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No