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Data Lakes

Multi-Cloud / Hybrid Data Lakes

Multi-cloud and hybrid data lakes provide flexibility, scalability, increased data availability, cost optimization, better data management, improved performance, and support for innovation. As a result, organizations are building resilient, efficient, and flexible data environments that can adapt to changing business needs and technological advances.
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How can Multi-Cloud and Hybrid Data Lakes be leveraged for enhanced flexibility, performance, and interoperability?

At C&F, our primary focus is ensuring the interoperability of multi-cloud and hybrid environments, which refers to the ability to seamlessly integrate, manage, and leverage services and data across multiple cloud platforms. The ability to seamlessly move data between different cloud platforms without significant rework by maintaining data integrity and ensuring data formats are compatible between clouds is critical. They also ensure that services from various cloud providers can communicate and collaborate using APIs, middleware, and standard protocols to facilitate service interaction. The biggest challenge is vendor-lock risk, where reliance on specific cloud services makes it difficult to switch providers. Therefore, we use open standards and protocols to ensure compatibility between different cloud platforms and deploy platforms that offer tools to manage multi-cloud and hybrid environments.

Flexibility and avoidance of vendor lock-in

Avoid dependence on a single provider by enabling seamless integration and movement of data and applications between multiple cloud providers to choose the best available services and pricing models.

Enhanced data availability and reliability

Improve data availability and reliability by distributing data across multiple clouds so that if one cloud provider experiences an outage, data and services will still be available from another provider.

Optimized cost management

Optimize costs by selecting the most cost-effective services from different providers. Manage workload allocation and reduce operational costs.

Improved performance and reduced latency

Process and store data closer to where it is generated or needed, reducing latency and improving performance for real-time processing applications.

Although the benefits of having hybrid environments seem apparent, building a resilient, efficient, and flexible multi-cloud data architecture is very challenging. To achieve this, we ensure seamless integration and data flow across cloud environments using standardized APIs, containerization, multi-cloud management platforms, middleware, and robust security practices. An essential but often overlooked component is optimizing network configurations and establishing comprehensive data management frameworks that enhance performance, security, and compliance.

Overview

In the era of big data, data storage is an essential consideration that requires flexibility, scalability, and cost-effectiveness. Initially, most businesses stored data in data warehouses, however as data amounts increased storage and management became more difficult. Data lakes emerged as an alternative to a data warehouse, able to store vast amounts of raw data in its native format, be it structured or unstructured data. Today, organizations are moving towards a multi-cloud hybrid data lake architecture that leverages more than one public cloud. Data stored in a hybrid-cloud data lake offers flexibility, cost-effectiveness, improved performance, and better data access and reliability. 

Experts in the field

Michał Majkowski
Principal Software Architect
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Piotr Drozd
Senior Director
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