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What is Digna?

digna is a next-generation data quality and observability platform designed to help organizations build trust in their data, detect issues early, and understand how their data behaves over time. As data environments grow in complexity, traditional monitoring approaches are no longer enough. digna goes beyond static checks and dashboards by combining observability with analytics, enabling teams to not only detect anomalies but also interpret patterns, trends, and changes in data behavior. Comprehensive Data Observability Across Your Entire Platform digna is built as a modular platform with five independent components that can be deployed together or separately, depending on your needs: * Data Anomalies — Detect unexpected changes in data volumes, distributions, and behavior using AI-driven anomaly detection without manual rules * Data Analytics — Understand trends, patterns, and seasonality through built-in time-series analysis * Data Timeliness — Monitor data delivery and ensure pipelines meet expected arrival times * Data Validation — Enforce data quality rules and compliance with flexible, scalable validation logic * Data Schema Tracker — Detect schema changes in real time to prevent pipeline failures and downstream issues Together, these modules provide full visibility into both data quality and business data behavior. Key Advantages * In-database processing ensures data never leaves your environment, supporting privacy, security, and regulatory compliance * AI-driven anomaly detection eliminates the need for manually defined rules * Built-in analytics capabilities enable teams to understand data trends and behavior without external tools * Scalable validation framework supports consistent data quality across complex data environments * Schema change tracking protects pipelines from breaking changes Designed for Modern Data Platforms digna integrates seamlessly with leading data platforms including Snowflake, Databricks, Teradata, and more.

What is Actian Data Observability?

Actian Data Observability is a cutting-edge platform that utilizes artificial intelligence to continuously monitor, validate, and uphold the integrity, quality, and reliability of data within modern data ecosystems. This platform features automated Data Observability Agents that evaluate the data as it flows into data lakehouses or warehouses, allowing for the detection of anomalies, clarification of root causes, and support for problem-solving before these issues can disrupt dashboards, reports, or AI applications. By offering real-time insights into data pipelines, it ensures that data remains accurate, complete, and trustworthy throughout its lifecycle. In contrast to conventional techniques that rely on sampling, this system eliminates blind spots by overseeing the full spectrum of data, enabling organizations to identify hidden errors that could undermine analytics or machine learning outcomes. Additionally, its built-in anomaly detection, powered by AI and machine learning, facilitates the prompt identification of irregularities, such as schema changes, data loss, or unexpected distributions, which accelerates the diagnosis and rectification of issues. Ultimately, this forward-thinking methodology greatly increases the confidence organizations have in their data-driven decisions, fostering a culture of data reliability and integrity. Furthermore, as companies continue to depend on data for strategic planning, such a robust observability framework becomes indispensable in navigating the complexities of today’s data landscape.

Media

Media

Integrations Supported

SQL Server
Snowflake
IBM Netezza Performance Server
MariaDB
MySQL
PostgreSQL Maestro

Integrations Supported

SQL Server
Snowflake
Amazon Redshift
Amazon S3
Apache Iceberg
Asana
Databricks
Delta Lake
Google Cloud BigQuery
Google Cloud Platform
IBM Db2
MongoDB
Oracle Cloud Infrastructure
SAP Cloud Platform
Splunk Cloud Platform
Tableau

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

digna GmbH

Date Founded

2019

Company Location

Austria

Company Website

www.digna.ai

Company Facts

Organization Name

Actian

Date Founded

1980

Company Location

United States

Company Website

www.actian.com/data-observability/

Categories and Features

AI Data Analytics

Not specified

AI Tools

Not specified

Anomaly Detection

Not specified

Data Management

Not specified

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Categories and Features

Data Observability

Not specified

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