All Webinars Videos Data Sheets Whitepapers Case Studies
Webinars
4 Best Practices to Achieve Hadoop Operational Excellence Across Multiple Big Data Technologies
Most organizations use multiple technologies to run a single data processing application including Hive, Spark, Oozie, H2O, etc. The challenge is how do you manage and monitor these data applications to ensure service levels are met? We go through 4 things you need in order to deliver Hadoop operations excellence. 30-min webinar
Reducing Hospital Readmissions with Big Data Predictive Analytics
Presented by guest speaker Michael Covert, CEO of Analytics Inside and Big Data expert, examines how Healthcare Providers are finding ways to use Big Data for predictive analytics to reduce readmission rates and improve operational efficiency while complying with regulatory mandates. He goes into detail about building a deep learning architecture using Cascading and Driven. 60-min webinar
How to Automate Offloading ETL Processes to Hadoop
Offloading expensive Data Warehouse ETL processes to Hadoop is often one of the first Big Data efforts but you have hundreds, maybe thousands, of legacy ETL processes to migrate which makes achieving ROI a distant goal. What if you could automatically convert up to 70% of your existing ETL processes to run on Hadoop with no code changes? 60-min webinar
How to Get Hadoop App Intelligence with Driven
You built Cascading/Scalding apps to mine all that data you collected in Hadoop. But just when you were seeing results, something went wrong — the app broke, data flows stopped, and business came to a halt.
How to Build Better Big Data Applications with Driven
Developing big data applications can be a complex task with multiple data sources, complex joins, filtering and cleansing steps. This complexity often makes it hard for developers to understand if they have connected all the pieces together properly and testing starts to become more art than science.
5 Best Practices to Achieve Operational Excellence for Hadoop Apps
Imagine if you could stop stringing together Hadoop Jobtracker, log files, and half a dozen other tools to try to understand what is happening with your big data applications.
How To Get Better Visibility into Your Hive and MapReduce Application Performance
Apache Hive queries and MapReduce jobs often experience performance issues and bottlenecks because of the multi-tenant nature of Hadoop and a lack of visibility into performance.
Learn From HomeAway Best Practices for Managing Hadoop DevOps
HomeAway, Inc. (NASDAQ:AWAY) is the world's leading online marketplace for the vacation rental industry. Operating through over 40 websites in 22 countries, HomeAway and its many subsidiaries, like VRBO, manage over 1M property listings.
Videos
Introducing Driven, APM for Big Data
This video provides a quick introduction to Driven, APM for Big Data. See how Driven can help you manage and monitor the performance of all your Hadoop and Spark applications. 90-sec Video
Driven 2-min Product Overview
Quick 2-min overview of the key capabilities of Driven, performance management for Big Data applications.
Data Sheets
BEST PRACTICES FOR MANAGING HIVE APPLICATION PERFORMANCE
Solution Brief
With success comes new challenges managing your growing number of Hive applications. You’re not alone if you are struggling to maintain a high quality of service to the business. We’ve interviewed hundreds of leading enterprises to understand how they use Driven to gain control and reliably meet service levels.
Performance Management for Cascading Applications
Cascading has emerged as a proven open source application development platform for building big data applications on Hadoop with more than 10,000 production deployments and growing.
Application Performance Management for Hadoop and Spark
Driven is the industry’s first performance management solution for Hadoop and Spark applications. It provides the deep insights and visibility you need to manage the performance of all your Big Data applications.
Whitepapers
Hadoop Performance Monitoring Tools: Whitepaper Comparison Guide

Solution Comparison Guide

Like all things Big Data, there are many choices for a Hadoop performance monitoring tools. To help you understand the differences between Pepperdata, Cloudera Manager, Apache Ambari and Driven, we’ve created this comparison guide of Hadoop performance monitoring tools so you can quickly assess the best solution to meet your needs.
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For a sneek peak, click here.
Smarter Big Data Application Performance Management
Anatomy of a Decision
We partnered with Blue Hill Research who held in-depth qualitative interviews with three leading organizations with advanced Big Data initiatives. The focus of the interviews was improving development efficiency and managing application performance in production environments. We offer these findings so that business decision-makers can understand the challenges and opportunities of peer organizations in pursuit of optimizing their own Big Data environment.
BEST PRACTICES FOR MANAGING HIVE APPLICATION PERFORMANCE
Solution Brief
With success comes new challenges managing your growing number of Hive applications. You’re not alone if you are struggling to maintain a high quality of service to the business. We’ve interviewed hundreds of leading enterprises to understand how they use Driven to gain control and reliably meet service levels.
Nine Best Practices for Achieving Operational Readiness on Hadoop
Enterprise IT teams are quickly discovering that running applications on Hadoop while maintaining enterprise-standards of quality, reliability, and governance is no easy task.
Case Studies
HomeAway Uses Cascading and Driven to Increase Booking Conversions
HomeAway is the world's leading online marketplace for the vacation rental industry. One of their first Hadoop projects was to improve rental booking conversion by analyzing results "a/b tests" from their various websites. They started developing MapReduce applications and quickly discovered they needed a better way.