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What is Promethium?

Promethium equips data and analytics teams with the tools to boost their productivity, ensuring they can adapt to the ever-increasing data volumes and the shifting requirements of the market. Simply establishing a connection to a data warehouse or lake for raw data access is insufficient for meeting contemporary standards. The task of refining datasets entails substantial effort from data teams, which are not growing at the same rate as the surge in data or the demand for insights. By utilizing Promethium, overburdened data teams can refine their workflows, resulting in quicker turnaround times. The platform significantly reduces the dependency on traditional ETL processes, allowing for immediate access to data in its original context. This decrease in data movement not only saves time but also reduces expenses. With Promethium, a single user can achieve in a few minutes what typically would take a team several months and a multitude of tools to complete. Users can easily connect and organize data sources, as well as generate and query cross-source datasets with just a few clicks, all without needing to write any code. This remarkable reduction in custom code and ETL processes facilitates real-time validation of data accuracy, thus eliminating the delays usually tied to lengthy ETL operations. Furthermore, the capability to share finalized work instantly cultivates a culture of reuse, negating the necessity for redundant analyses. These functionalities not only simplify processes but also significantly improve collaboration among team members, enhancing overall productivity and innovation.

What is Dremio?

Dremio offers rapid query capabilities along with a self-service semantic layer that interacts directly with your data lake storage, eliminating the need to transfer data into exclusive data warehouses, and avoiding the use of cubes, aggregation tables, or extracts. This empowers data architects with both flexibility and control while providing data consumers with a self-service experience. By leveraging technologies such as Apache Arrow, Data Reflections, Columnar Cloud Cache (C3), and Predictive Pipelining, Dremio simplifies the process of querying data stored in your lake. An abstraction layer facilitates the application of security and business context by IT, enabling analysts and data scientists to access and explore data freely, thus allowing for the creation of new virtual datasets. Additionally, Dremio's semantic layer acts as an integrated, searchable catalog that indexes all metadata, making it easier for business users to interpret their data effectively. This semantic layer comprises virtual datasets and spaces that are both indexed and searchable, ensuring a seamless experience for users looking to derive insights from their data. Overall, Dremio not only streamlines data access but also enhances collaboration among various stakeholders within an organization.

Media

Media

Integrations Supported

Looker
Microsoft Power BI
Tableau
Apache Superset
Athena Archiver
Collibra
DataClarity Unlimited Analytics
Emgage
HPE Ezmeral
Hadoop
Hex
Oracle Cloud Infrastructure
Privacera
PuppyGraph
Snowflake
Strategy ONE
Yurbi
data.world
witboost

Integrations Supported

Looker
Microsoft Power BI
Tableau
Apache Superset
Athena Archiver
Collibra
DataClarity Unlimited Analytics
Emgage
HPE Ezmeral
Hadoop
Hex
Oracle Cloud Infrastructure
Privacera
PuppyGraph
Snowflake
Strategy ONE
Yurbi
data.world
witboost

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Promethium

Date Founded

2018

Company Location

United States

Company Website

www.pm61data.com

Company Facts

Organization Name

Dremio

Date Founded

2015

Company Location

United States

Company Website

www.dremio.com

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Lineage

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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