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What is Apache Atlas?

Atlas is a powerful and flexible suite of crucial governance services that enables organizations to meet their compliance requirements effectively within Hadoop, while also integrating smoothly with the larger enterprise data environment. Apache Atlas equips organizations with the tools to oversee open metadata and governance, allowing them to build an extensive catalog of their data assets, classify and manage these resources, and encourage collaboration among data scientists, analysts, and the governance team. It comes with predefined types for a wide range of metadata relevant to both Hadoop and non-Hadoop settings, and it also allows for the creation of custom types to better handle metadata management. These custom types can include basic attributes, complex attributes, and references to objects, and they can inherit features from other types. Entities serve as instances of these types, containing specific details about the metadata objects and their relationships. Moreover, the provision of REST APIs streamlines interaction with types and instances, thereby improving the overall connectivity and functionality within the data framework. This holistic strategy guarantees that organizations can adeptly manage their data governance requirements while remaining responsive to changing demands, ultimately leading to more effective data stewardship. Furthermore, by utilizing Atlas, organizations can enhance their data integrity and compliance efforts, further strengthening their operational resilience.

What is Aggua?

Aggua functions as an AI-enhanced data fabric platform aimed at equipping both data and business teams with easy access to their information, building trust, and providing actionable insights for more informed decision-making based on data. With just a few clicks, you can uncover essential details about your organization's data framework instead of remaining unaware of its complexities. Obtain insights into data costs, lineage, and documentation effortlessly, allowing your data engineers to maintain their productivity without interruptions. Instead of spending excessive time analyzing how changes in data types affect your pipelines, tables, and overall infrastructure, automated lineage facilitates your data architects and engineers in reducing the time spent on manual log checks, allowing them to concentrate on implementing necessary infrastructure improvements more effectively. This transition not only simplifies operations but also fosters better collaboration among teams, leading to a more agile and responsive approach to tackling data-related issues. Additionally, the platform ensures that all users, regardless of their technical background, can engage with data confidently and contribute to an organization's data strategy.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Azure Data Lake
Beats
Hackolade
Hadoop
Hive Data
Hue
JanusGraph
Occubee
Spark

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
Snowflake

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

atlas.apache.org/#/

Company Facts

Organization Name

Aggua

Date Founded

2020

Company Location

United States

Company Website

www.aggua.io

Categories and Features

Data Catalog

Not specified

Data Governance

Not specified

Data Lineage

Not specified

Data Masking

Not specified

Metadata Management

Not specified

Categories and Features

Data Catalog

Not specified

Data Engineering

Not specified

Data Fabric

Not specified

Data Governance

Not specified

Data Lineage

Not specified

Data Management

Not specified

Data Mapping

Not specified

Data Observability

Not specified

Data Quality

Not specified

Metadata Management

Not specified

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