Amazon EMR Migration
Reduce the cost and dramatically increase the performance of your Big Data Solution on Apache Hadoop/Spark by migrating to Amazon EMR
Why Amazon EMR?
A cost-efficient, high-performance service to improve the resource utilization by Apache Hadoop, Hive, Spark, Map/Reduce, and Machine Learning workloads.
IDC proves the economic benefits of
migrating Apache Hadoop and Spark to Amazon EMR
Business Value Highlights
reduced cost of ownership
months to breakeven
Technology Value Highlights
reduction in unplanned downtime
more efficient Big Data teams
more efficient Big Data/Hadoop management staff
Referenced IDC White Paper: “The Economic Benefits of Migrating Apache Spark and Hadoop to Amazon EMR“
Quickly and cost-effectively process and drive intelligence from large amounts of data
Scale-out or back in the worker nodes of purpose managed separate clusters for ephemeral, long-running, and smaller workloads. This feature enables pay-per-use versus often idle large cluster.
Amazon EMR's built-in Auto Scaling increases the performance of various types of workloads while keeping the overall cost low. This feature also improves the price-performance ratio.
Reduced Operational Cost
EMR's automated cluster provisioning i.e., cluster setup, Hadoop configuration, and cluster tuning reduce overall operational cost. This feature also improves your Operation team’s productivity.
Efficient Data Storage
Amazon S3 is an 11 9s availability storage for various data types. It separates storage and compute, to manage multi-tenancy for both performance and chargeback to different business units.
New Product Development
Extract Transform Load (ETL)
Core Migration Scenarios
We help migrate on-premises Hadoop and Spark to Amazon EMR
Hadoop distribution on-premises to Amazon EMR. This migration pattern is also referred to as Lift-and-Shift.
Hadoop distribution on-premises to Amazon EMR with new architecture and complementary services to provide additional functionality, scalability, reduced cost, and flexibility.
Moving Hadoop workload from on-premises to AWS but with a new architecture that may include Containers, non-HDFS, Streaming, etc. The workload remains the same, or add new cutting-edge functionality.
Migration Considerations We Address
Significant improvement in price-performance ratio
Management of Ephemeral and non-Ephemeral clusters
Data migration challenges related to data volume, variety, velocity, and veracity
Zero downtime for downstream application via an organized cutover process
Challenges of building a robust provisioning pipeline
High availability and disaster recovery
Not sure how to kick off the migration? Request an Amazon EMR Migration WorkshopDownload The Agenda
AWS Big Data Competency Partner
Provectus is an AWS Premier Consulting Partner. AWS Data & Analytics, DevOps, and Machine Learning Competency Partner.
From Apache Hadoop/Spark to Amazon EMR: Best Migration Practices and Cost Optimization Strategies
Find out how organizations drive better business and technology outcomes by migrating on-premises Apache Hadoop/Spark to Amazon EMR.
Data Infrastructure Migration and Modernization
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