59 min

Speed Up And Simplify Your Streaming Data Workloads With Red Panda Data Engineering Podcast

    • Technology

Summary
Kafka has become a de facto standard interface for building decoupled systems and working with streaming data. Despite its widespread popularity, there are numerous accounts of the difficulty that operators face in keeping it reliable and performant, or trying to scale an installation. To make the benefits of the Kafka ecosystem more accessible and reduce the operational burden, Alexander Gallego and his team at Vectorized created the Red Panda engine. In this episode he explains how they engineered a drop-in replacement for Kafka, replicating the numerous APIs, that can scale more easily and deliver consistently low latencies with a much lower hardware footprint. He also shares some of the areas of innovation that they have found to help foster the next wave of streaming applications while working within the constraints of the existing Kafka interfaces. This was a fascinating conversation with an energetic and enthusiastic engineer and founder about the challenges and opportunities in the realm of streaming data.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management
What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise.
When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance? How much time could you save if those tasks were automated across your cloud platforms? Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud. Our comprehensive data-level security, auditing and de-identification features eliminate the need for time-consuming manual processes and our focus on data and compliance team collaboration empowers you to deliver quick and valuable data analytics on the most sensitive data to unlock the full potential of your cloud data platforms. Learn how we streamline and accelerate manual processes to help you derive real results from your data at dataengineeringpodcast.com/immuta.
If you’re looking for a way to optimize your data engineering pipeline – with instant query performance – look no further than Qubz. Qubz is next-generation OLAP technology built for the scale of Big Data from UST Global, a renowned digital services provider. Qubz lets users and enterprises analyze data on the cloud and on-premise, with blazing speed, while eliminating the complex engineering required to operationalize analytics at scale. With an emphasis on visual data engineering, connectors for all major BI tools and data sources, Qubz allow users to query OLAP cubes with sub-second response times on hundreds of billions of rows. To learn more, and sign up for a free demo, visit dataengineeringpodcast.com/qubz.
You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data platforms. For more opportunities t

Summary
Kafka has become a de facto standard interface for building decoupled systems and working with streaming data. Despite its widespread popularity, there are numerous accounts of the difficulty that operators face in keeping it reliable and performant, or trying to scale an installation. To make the benefits of the Kafka ecosystem more accessible and reduce the operational burden, Alexander Gallego and his team at Vectorized created the Red Panda engine. In this episode he explains how they engineered a drop-in replacement for Kafka, replicating the numerous APIs, that can scale more easily and deliver consistently low latencies with a much lower hardware footprint. He also shares some of the areas of innovation that they have found to help foster the next wave of streaming applications while working within the constraints of the existing Kafka interfaces. This was a fascinating conversation with an energetic and enthusiastic engineer and founder about the challenges and opportunities in the realm of streaming data.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management
What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise.
When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance? How much time could you save if those tasks were automated across your cloud platforms? Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud. Our comprehensive data-level security, auditing and de-identification features eliminate the need for time-consuming manual processes and our focus on data and compliance team collaboration empowers you to deliver quick and valuable data analytics on the most sensitive data to unlock the full potential of your cloud data platforms. Learn how we streamline and accelerate manual processes to help you derive real results from your data at dataengineeringpodcast.com/immuta.
If you’re looking for a way to optimize your data engineering pipeline – with instant query performance – look no further than Qubz. Qubz is next-generation OLAP technology built for the scale of Big Data from UST Global, a renowned digital services provider. Qubz lets users and enterprises analyze data on the cloud and on-premise, with blazing speed, while eliminating the complex engineering required to operationalize analytics at scale. With an emphasis on visual data engineering, connectors for all major BI tools and data sources, Qubz allow users to query OLAP cubes with sub-second response times on hundreds of billions of rows. To learn more, and sign up for a free demo, visit dataengineeringpodcast.com/qubz.
You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data platforms. For more opportunities t

59 min

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