Category: Amazon EMR

When designing IT solutions, a one-size-fits-all approach misses opportunities for performance and cost savings. Exxeta proposes a use-case driven architecture approach that fits IT components to specific business processes. A real-world example shows how this approach helped an automotive company build a high-performance, scalable analytics solution at a lower cost by utilizing fit-for-purpose technologies like Apache HBase and Amazon S3.

A global technology firm migrated its massive on-premises Apache Hadoop data center to Amazon EMR and achieved major cost savings and capabilities. By deploying Pepperdata’s optimization software, which works in real-time to maximize resource utilization, the firm achieved nearly 25% additional cost reduction on top of its Amazon EMR savings, without any code changes or manual tuning. Learn how Pepperdata Capacity Optimizer rapidly identifies existing nodes where more jobs could be completed.

As technology advances and business requirements change, organizations may find themselves needing to migrate away from legacy data processing systems like HBase, Solr, and HBase Indexer. Explore the advantages of migrating from HBase, Solr, and HBase indexer to a modern data ecosystem based on AWS, and dive deep on the discuss architecture, design, and pathways for implementation. This post offers insights and guidance from Rackspace for those looking to embark on this intricate migration journey.

Online analytical processing (OLAP) is a method of organizing datasets in a multi-dimensional format for quick analysis and provides deeper insights for decision-makers. Multi-dimension analysis is widely adopted by analysts, knowledge users, and power users for their decision support process. Learn how utilizing AWS analytic services and migration tools together with HCLTech frameworks to orchestrate OLAP solutions.

Learn how to leverage Apache Iceberg capabilities with Dremio and Amazon EMR Serverless to scale your business by keeping up with various changes to your data and analytics portfolio. Iceberg is a high-performance, open table format for huge analytical tables specifically designed to mitigate the challenges introduced by unforeseen changes observed by enterprises. Dremio is a data lake engine that delivers fast query speed and a self-service semantic layer operating directly against Amazon S3 data.

Gogo is a global provider of broadband connectivity products and services for business aviation. It needed a qualified engineering team to undertake a complete transition of its solutions to the cloud, build a unified data platform, and streamline the best speed of the inflight internet. Learn how N-iX developed the data platform on AWS that aggregates data from over 20 different sources using Apache Spark on Amazon EMR.

Take an in-depth view of the cloud migration and data platform modernization process for Flipboard, which engaged Mactores Cognition for a thorough assessment of the self-managed platform and help migrating existing data workloads to a fully managed Amazon EMR serverless big data platform. The process streamlined Flipboard’s distributed database capabilities, allowing the social media platform to support user spikes at scale, maximize throughput performance, and prepare to expand the user base exponentially.

Provectus, an AWS Premier Tier Services Partner with the Data and Analytics Competency, helps clients resolve issues of their legacy, on-premises data platforms by implementing best practices for the migration and optimization of Amazon EMR workloads. This post examines the challenges organizations face along the path to a successful migration, and explores best practices for re-architecting and migrating on-premises data platforms to AWS

Data is growing in all aspects of our world; every vertical and technical domain is being pushed to the limit by growing data—geospatial is no exception. Learn about Esri’s ArcGIS GeoAnalytics Engine on Amazon EMR and how its geospatial capabilities can complement your current analytics workflows. GeoAnalytics seamlessly integrates with Amazon EMR and can be deployed with an Esri-provided bootstrap script at EMR cluster creation.

While the global Hadoop-as-a-service market size is growing at a CAGR of ~39%, it leaves out many small, mid, and large-scale organizational players due to the inherent pains of migration. This post explores how Virtusa complements Amazon EMR Migration by providing approaches and utilities to streamline and manage large-scale Hadoop-to-Amazon EMR migrations by creating a migration framework of automated modules.