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

57%

reduced cost of ownership

342%

five-year ROI

8

months to breakeven

Technology Value Highlights

99%

reduction in unplanned downtime

33%

more efficient Big Data teams

46%

more efficient Big Data/Hadoop management staff

Key Features

Quickly and cost-effectively process and drive intelligence from large amounts of data

Cost Efficiency

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.

High Performance

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.

Use Cases

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New Product Development

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Extract Transform Load (ETL)

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Clickstream Analysis

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Real-Time Streaming

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Interactive Analytics

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Genomicso

Core Migration Scenarios

We help migrate on-premises Hadoop and Spark to Amazon EMR

#1

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Re-Purchase

Hadoop distribution on-premises to Amazon EMR. This migration pattern is also referred to as Lift-and-Shift.

#2

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Re-Architect

Hadoop distribution on-premises to Amazon EMR with new architecture and complementary services to provide additional functionality, scalability, reduced cost, and flexibility.

#3

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NextGen Architecture

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

01.

Significant improvement in price-performance ratio

02.

Management of Ephemeral and non-Ephemeral clusters

03.

Data migration challenges related to data volume, variety, velocity, and veracity

04.

Zero downtime for downstream application via an organized cutover process

05.

Challenges of building a robust provisioning pipeline

06.

High availability and disaster recovery

AWS Big Data Competency Partner

Provectus is an AWS-certified Consulting Partner. AWS Data & Analytics, DevOps, and Machine Learning Competency Partner.

Contact Us Today

Jumpstart Your Migration to Amazon EMR!

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