Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Teradata VantageCloud Reviews & Ratings
    1,107 Ratings
    Company Website
  • DataHub Reviews & Ratings
    10 Ratings
    Company Website
  • Snowflake Reviews & Ratings
    1,417 Ratings
    Company Website
  • Google Cloud Platform Reviews & Ratings
    60,933 Ratings
    Company Website
  • dbt Reviews & Ratings
    251 Ratings
    Company Website
  • AnalyticsCreator Reviews & Ratings
    46 Ratings
    Company Website
  • DbVisualizer Reviews & Ratings
    565 Ratings
    Company Website
  • DataBuck Reviews & Ratings
    6 Ratings
    Company Website
  • D&B Connect Reviews & Ratings
    188 Ratings
    Company Website
  • Semarchy xDM Reviews & Ratings
    64 Ratings
    Company Website

What is IOMETE?

IOMETE is a self-hosted sovereign data platform designed to support enterprise data analytics, large-scale processing, and artificial intelligence workloads. The platform provides a modern data lakehouse architecture that combines storage, analytics, and machine learning capabilities into a single integrated environment. Organizations can deploy IOMETE across on-premises infrastructure, private cloud environments, public clouds, or hybrid deployments, giving them complete control over where their data resides. This deployment flexibility allows companies to maintain data sovereignty and compliance while avoiding vendor lock-in associated with traditional SaaS data platforms. The system includes a wide range of data engineering and analytics tools such as SQL editors, Jupyter notebooks, distributed Spark processing, and workflow orchestration engines. IOMETE also features a centralized data catalog that enables teams to discover datasets, manage metadata, and maintain data lineage across projects. Built-in governance and security tools allow organizations to control access permissions at granular levels, including tables, rows, columns, and user groups. The platform supports the data mesh approach by allowing organizations to organize data into domains and enable self-service data access across teams. By minimizing data movement and enabling processing directly within the customer’s infrastructure, IOMETE helps reduce operational costs and improve data security. Its architecture is designed to handle large-scale datasets while supporting analytics, reporting, and AI model development. The platform also integrates with external business intelligence tools through SQL endpoints for visualization and reporting. Overall, IOMETE provides enterprises with a scalable and secure data foundation for managing the growing demands of modern analytics and AI-driven applications.

What is Deequ?

Deequ is a groundbreaking library designed to enhance Apache Spark by enabling "unit tests for data," which helps evaluate the quality of large datasets. User feedback and contributions are highly encouraged as we strive to improve the library. The operation of Deequ requires Java 8, and it is crucial to recognize that version 2.x of Deequ is only compatible with Spark 3.1, creating a dependency between the two. Users of older Spark versions should opt for Deequ 1.x, which is available in the legacy-spark-3.0 branch. Moreover, we also provide legacy releases that support Apache Spark versions from 2.2.x to 3.0.x. The Spark versions 2.2.x and 2.3.x utilize Scala 2.11, while the 2.4.x, 3.0.x, and 3.1.x releases rely on Scala 2.12. Deequ's main objective is to conduct "unit-testing" on data to pinpoint possible issues at an early stage, thereby ensuring that mistakes are rectified before the data is utilized by consuming systems or machine learning algorithms. In the upcoming sections, we will illustrate a straightforward example that showcases the essential features of our library, emphasizing its user-friendly nature and its role in preserving data quality. This example will also reveal how Deequ can simplify the process of maintaining high standards in data management.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Apache Spark
Looker
Tableau

Integrations Supported

Amazon Web Services (AWS)
Apache Spark
Looker
Tableau

API Availability

Has API

API Availability

Has API

Pricing Information

Free
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

IOMETE

Date Founded

2020

Company Location

United States

Company Website

iomete.com

Company Facts

Organization Name

Deequ

Company Website

github.com/awslabs/deequ

Categories and Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

Categories and Features

Popular Alternatives

Popular Alternatives

Spark Streaming Reviews & Ratings

Spark Streaming

Apache Software Foundation
Apache Spark Reviews & Ratings

Apache Spark

Apache Software Foundation
MLlib Reviews & Ratings

MLlib

Apache Software Foundation
Apache Mahout Reviews & Ratings

Apache Mahout

Apache Software Foundation