Zaloni Zip: Solving the Challenges of Hybrid Data Lake Architecture

February 14, 2017 Parth Patel

In this Zaloni Zip, we will discuss the challenges of a Hybrid Data Lake architecture and how Zaloni’s centralized data-lake management platform tackles those challenges head-on. 


Migration to cloud is unavoidable for Enterprise IT in today’s world. Enterprises, big or small, are adopting and leveraging public/private cloud technologies to reduce their infrastructure footprint by shifting on-premises ETL workloads to public clouds such as AWS and Azure.

Yet, many organizations are not in favor of total migration to cloud. Each have their reasons, some have data security, governance, and regulatory compliance concerns, while others have available resources on their existing on-prem infrastructure.

This introduces a concept of hybrid data-lake architecture, consisting of public cloud, and on-prem systems. But, this approach also creates a very complex data platform as data resides in multiple disparate systems.

The challenge of hybrid data-lake management is real. Organizations are looking for a single, unified data-management platform which provides them data accessibility and scalability along with security, governance, and operational control.

Remove the Boundaries Between On-Prem and Cloud

Adopting a hybrid architecture for your data lake does not mean one has to sacrifice the value and performance derived from your data that resides in disparate sources. Zaloni’s data lake management platform provides organizations with a centralized data management platform, allowing them to seamlessly connect to any data source on-prem or in cloud, building a logical data-lake. Key benefits include:

  • Improved performance by removing data silos.
  • Visual work-flow designer and transformation engine enables enterprises to design pipelines from ingestion to analytics.
  • Metadata-driven architecture serves as the foundation for data quality, governance, mastering, and security.
  • Microservice-based architecture that enables easy scalability and allows use of transient cloud clusters, delivering agility and cost-savings.
These benefits are delivered via a simple, easy-to-use web interface. For more information read our blog or visit the platform page.

About the Author

Parth  Patel

Big Data Solutions Engineer - RTP Raleigh NC

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