Our Customers

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Last week marked three years for me at Pepperdata and it’s amazing the progress we’ve made as a company in the last few years. We’ve been fortunate to see more than 100% growth year-over-year and I thought in this post I would reflect on some of the reasons why customers work with Pepperdata.

Multi-tenancy is hard. All of our customers operate multi-tenant platforms, most at large scale, and that’s very challenging. Hundreds of users and tens of thousands of jobs per ...

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My Key Takeaways from Strata Data Conference NYC

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Thousands of developers, data engineers, data scientists, and business professionals attended Strata Data Conference last week in New York City. Events like these allow us to speak directly with customers, partners, and prospects on a range of issues: What Big Data projects are they working on? What are their biggest challenges and concerns? What trends are they seeing in the industry?

I wanted to share some of my observations and takeaways from last week based on the conference sessions I attended, ...

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New Program Serves Systems Integration Service Providers in Big Data and DevOps Market

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Earlier in the week, we announced the Pepperdata Partner Program to recognize qualified partners and help our customers accelerate and maximize the benefits of using the Pepperdata product suite. This strategic program will include partners who demonstrate a high level of expertise in successfully implementing and using the Pepperdata suite of operator and developer applications. Our new partners are industry leaders who understand Big Data and bring expertise to ensure customers can rapidly deploy Pepperdata to solve their challenges and ...

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Six Key Takeaways from Spark Summit and DataWorks Summit

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It’s been an extremely busy–but, very productive – couple of weeks. Pepperdata sponsored two critically important events attended by many of our clients and target customers.

Thousands of developers, data engineers, data scientist and business professionals attended each event. Spark Summit is dubbed the world’s largest event for the Apache Spark community, and DataWorks Summit is one of the industry’s premier big data community events. Combined, these events promote the opportunity to participate in hundreds of formal presentations as well as ...

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Solving Performance Bottlenecks for Developers—Introducing Pepperdata Code Analyzer for Spark

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Two years ago, IBM made a $300 million commitment to Spark. The investment shows how Spark has grown from its humble beginnings at UC Berkeley as an AMPLab project to a production-grade open source project. More importantly, it demonstrates an urgency around Spark as it sees continued enterprise adoption.

I witnessed Spark’s momentum firsthand as one of its earliest adopters. I first came across Spark back in 2011 as a founder at ...

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The Big Data Insiders: Q & A with Ian O’Connell

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As discussed in our last blog, Apache Spark has become the big thing in Big Data. As the largest open source community in Big Data, Spark enables flexible in-memory data processing and advanced analytics on the Hadoop platform. The roster of companies that have adopted Spark and also are project committers includes some of tech’s biggest names, such as Facebook, Netflix, Yahoo, IBM and Intel.

In the first installment of “The Big Data Insiders” — interviews with Big Data experts and ...

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Pepperdata Digs into Production Spark with the Experts

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Apache Spark has quickly become an open source framework with widespread appeal for large-scale data processing. Last year, more than 1,000 organizations were using Spark in production. Many run Spark on clusters of thousands of nodes and up to petabytes of data, according to the project’s FAQ. Another indicator of its growth: according to Indeed, Spark-related job postings are up more than 10x over the past two years.

But beyond the impressive numbers, what users say about production Spark ...

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Performance is the Difference Between Business Critical and Business Useless – Introducing Pepperdata Application Profiler

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Big Data systems by their very nature are complex entities. This is because everything about them is super-sized: the data volume, the number of machines, and the velocity of the data. As a result, building production Big Data systems is difficult. It requires developing new intuition about both development and operations.  And, it requires the realization that performance is paramount.  

Over the past several years, Pepperdata has been helping our customers integrate a deep understanding of ...

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Introducing the Pepperdata Technology Advisory Board

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Today we announced our all-star Technology Advisory Board, an exclusive network of forward-thinking experts coming together to help shape the future direction of Pepperdata. The Board is made up of four industry and academic luminaries whom I greatly respect and admire. Our new board members not only understand Big Data, but also know how to build systems at scale.

Bringing backgrounds in designing, building and managing systems at scale for enterprises such as BlackRock, Credit Suisse, Stripe, Twitter and VMware, as ...

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We just made Amazon EMR up to 4x faster (for the same amount of money)

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The popularity of Amazon Elastic MapReduce (EMR) has soared over the last couple of years thanks to its ability to simplify big data processing. EMR provides a managed Hadoop framework that makes it easy, fast, and cost-effective for customers to distribute and process vast amounts of data – but all good things can be improved upon.

Today we are announcing a new offering that enables customers using Amazon EMR to run jobs up to four times faster ...

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