Apache Atlas

Apache Atlas is a scalable and extensible set of core foundational governance services that enables enterprises to effectively and efficiently meet their compliance requirements within Hadoop and allows integration with the whole enterprise data ecosystem. It is designed with an intention to manage and provide insights into data stored within and across multiple platforms and environments, including on-premises servers, cloud-based storage, and hybrid configurations.

History

Apache Atlas was first announced by Hortonworks in 2015. Its development was driven by the need for a comprehensive approach to data governance, security, and compliance in Hadoop environments. It entered the Apache Incubator in May 2015 and graduated as a top-level project in December 2017.

Functionality and Features

Apache Atlas offers features including metadata tagging, policy enforcement, lineage tracking, and data discovery. It allows data classification, centralized auditing, search and lineage, security, and encryption, and is extensible and embeddable through its well-defined APIs.

Architecture

The core components of Apache Atlas include the Graph Store, Type System, and Index Store. The Graph Store is designed to store metadata instances, the Type System provides a way to register models and instances, while the Index Store allows for rich search functionality.

Benefits and Use Cases

Apache Atlas is mainly used by organizations with stringent data governance needs. Its use cases include providing insight into the lineage of data, managing metadata, enforcing data security, and driving compliance in Hadoop clusters.

Challenges and Limitations

While Apache Atlas is highly beneficial, it has limitations including complex setup, lack of support for non-Hadoop platforms, and limited community support.

Comparison and Integration with Data Lakehouse

Data Lakehouses combine the storage capabilities of data lakes with the data management features of data warehouses. Apache Atlas, when integrated with a Data Lakehouse setup, can provide enhanced data governance capabilities. It governs data within the Data Lakehouse, providing comprehensive visibility into data origin, movement, and transformations.

Security Aspects

Apache Atlas provides security through its integration with Apache Ranger for policy enforcement. It provides features like metadata security and access control.

Performance

The performance of Apache Atlas is determined by its ability to manage, discover, and analyze large volumes of data without impacting the performance of the Hadoop cluster.

FAQs

Is Apache Atlas exclusive to Hadoop? Apache Atlas was designed primarily for Hadoop, but it also provides connectors for platforms outside the Hadoop ecosystem.

Does Apache Atlas provide real-time data governance? Apache Atlas provides near real-time data governance, depending on the complexity and volume of the data.

Glossary

Data Lakehouse: A hybrid of data lakes and data warehouses, combining the benefits of both.

Data Governance: The overall management of the availability, usability, integrity, and security of data used in an enterprise.

Metadata: Data that provides information about other data.

Data Lineage: These are the data life-cycle steps, which include the data's origins and where it moves over time.

Data Compliance: The act of adhering to and demonstrating adherence to a standard or regulation related to data management.

Dremio and Apache Atlas