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Apache Hadoop to AWS EMR Migration – All You Need to Know

What is the need for AWS EMR Migration?

Organizations worldwide are aware about the power of data analytics and processing frameworks, such as Apache Hadoop. However, challenges remain in the implementation and operation of these frameworks in data lake environments deployed on-premises. AWS EMR migration helps organizations shift their Hadoop deployments and big data workloads within budget and timeline estimates.

AWS EMR is recognized by Forrester as the best solution for migrating Hadoop platforms to the cloud. Upgrading and scaling hardware to accommodate growing workloads on-premises involves significant downtimes and is not economically feasible. This has further prompted organizations to re-architect using AWS EMR to build a modern system that is future-ready, high-performing, and cost-effective.

Challenges with Hadoop On-Premises

Scalability is challenging for organizations with Hadoop deployed on-premises as it involves the purchase of extra hardware. Additionally, it resists achieving elasticity and utilizing clusters for longer durations. The costs associated with workloads keep on increasing due to the ‘always on’ infrastructure while the data recovery and high availability must be managed manually.

The Need of the Hour for Organizations

  • Easily scalable and flexible infrastructure that can be quickly provisioned as per requirements.
  • Reduced admin dependency with a completely managed service.
  • Cost optimization with the ability to switch the infrastructure on and off based on workload requirements.
  • Innovative schemes for improved return on investment (ROI) in the long term.
  • Exploring new open-source technologies by spinning up sandboxes in real-time.
  • Integrating cloud security with the Hadoop ecosystem.

Why AWS EMR Migration?

Data-driven insights and cost optimization are primary considerations of organizations to achieve near-zero downtime of workloads with faster business value. Following are some key USPs of AWS EMR migration design that help organizations achieve the aforementioned.

  • Decoupling of the storage and compute systems.
  • A seamless data lake environment with Amazon S3.
  • A stateless compute infrastructure.
  • Cluster capabilities that are consistent and transient.
  • Cluster fragmentation based on business units for improved isolation, customization, and cost allocation.

Preferred Strategies for Hadoop to EMR Migration

Lift and Shift

This strategy helps companies achieve Hadoop to EMR migration faster to accelerate decommissioning of their on-premises data center. This enables organizations to eliminate cost-intensive hardware upgrades. The lift and shift strategy guides organizations to keep their existing Hadoop segregated and classified by utilizing AWS S3. Additionally, it helps them in decoupling resources, limiting code transformations to bare minimum. The simple lift and shift Hadoop to EMR migration approach moves the code as is to the cloud environment.


The replatform strategy for Hadoop to EMR migration enables organizations to maximize their cloud migration advantages. This is basically done by utilizing the entire set of features provided by AWS EMR. With this strategy, organizations can fine tune their workloads and infrastructure for cost-effectiveness, scalability, and performance. Additionally, this strategy allows organizations to integrate their Hadoop ecosystem with cloud monitoring and security. Although replatform is similar to the lift and shift approach, it offers relatively lesser optimizations when it comes to cloud features and offerings.


The strategy of re-architecting Hadoop on AWS EMR helps organizations to re-imagine their ecosystem of insights in the cloud. It helps them democratize their data to a larger customer pool while reducing the time-to-insight. This can be primarily attributed to the capabilities of streaming analytics, which provides organizations to self-service their requirements while building greater capabilities.

The re-architect strategy covers resolving all challenges of organizations, ranging from the analysis of business priorities to building a cloud-based data platform. The strategy basically involves changing the architecture with the help of cloud-native services to enhance performance, provision scalable solutions, and improve cost effectiveness of the infrastructure.

To Sum Up

Apache Hadoop to AWS EMR migration is best suited for organizations with long-term objectives. With this migration, organizations can re-architect their existing infrastructure with AWS cloud services such as S3, Athena, Lake Formation, Redshift, and Glue Catalog. Organizations that look for achieving easy, faster scalability and elasticity with better cluster utilization must prefer AWS EMR migration. This further helps them in realizing cost optimization and implementing a well-architected solution.

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