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Top 5 Reasons Customers Choose Bigstream to Accelerate Spark in the Cloud

The adoption of big data analytics in the cloud is well underway. Five to 10 years ago, it was hard to imagine housing and managing large volumes of data in a public cloud. Times have changed, though, and the cloud options have evolved to meet enterprise needs, particularly around performance, security, and reliability.
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Blog

Profiling and Optimizing ELT with Bigstream’s xRay and Hyperacceleration

Although extract, load, and transform (ELT) workloads have been around for ages, they still comprise some of the biggest challenges that Apache Spark™ users bring to us. Like with all applications that process large data sets, ELT performance problems create delayed results, missed deadlines, and even low morale.
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Blog

How One IoT Company Improved Apache Spark™ Performance Sixfold

IOT pipelines are compute-intensive. Apache Spark performance is often put to the test in these scaled environments. Learn how a Bigstream IOT customer was able to improve its Spark workflow Sixfold.
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Blog

How Adding Hyperacceleration Can Deliver the Business Value That Apache Spark™ Has Promised

Nearly every CEO aspires to make their company data-driven, infuse a data culture, and advance along the data maturity curve. If they fail, their board of directors will seek someone who can harness the value of data. Companies and other organizations succeeding on this path have invested in both the skills and culture, but also a fair amount of technology. Data is top of mind, not just for the CEO, but also for leaders throughout the organization.
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Blog

Hardware Acceleration for Big Data Analytics: How Your Enterprise Can Achieve Better Performance

Every organization wants to be all-in on digital transformation, seeking to dive deep into its big data platforms to drive efficiency and optimization. As these efforts become more critical to your enterprise, the priority becomes building an infrastructure that can meet the demand for a much higher computational power. CPU clustering has been one avenue, but Moore’s law is no longer applicable.
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Blog

FPGA vs. GPU Acceleration: Considering Performance/Power

To improve the performance of compute infrastructure and to keep up with the expanding requirements of data analytics and AI, many enterprises are looking to hardware acceleration as a integral solution. In most situations, advanced programmable hardware—mainly GPUs and FPGAs—is the primary source of acceleration. By using this advanced hardware, enterprises are gaining computational advantages; however, there are still reasonable concerns related to the difficulty of programming this specific hardware.
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Blog

FPGA vs. GPU Acceleration: Considering Performance/Price

Hardware-based acceleration is becoming a more important approach for improving the performance of compute infrastructure, addressing the growing needs of data analytics and AI. Typically, acceleration occurs via some form of advanced programmable hardware, such as a GPU or FPGA. This provides computational advantages, including application specificity of hardware, over general-purpose CPUs. A principal concern is the programming of advanced hardware and its difficulty.
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Press Release

Bigstream Closes Funding Round Led by Xilinx and Cota Capital, with Samsung and SK hynix

MOUNTAIN VIEW, CA, April 29, 2020/PRNewswire/ — Bigstream announced it has completed a $19.1 million funding round led by new investor Xilinx and existing investor Cota Capital, with participation from Samsung and SK hynix.
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Announcements

Bigstream - Engineering Roots

The idea for Bigstream and hyperacceleration goes back to 2015. Below is an interview with founder Maysam Lavasani about the vision. What is hyperacceleration? What does it mean for data scientists, data engineers, DevOps teams and application architects? 
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