In this episode of Simplyblock's Cloud Commute Podcast, Yingjun Wu, founder of RisingWave Labs, discusses stream processing and how RisingWave enables real-time data analytics. He explains the differences between batch and streaming databases, RisingWave’s PostgreSQL compatibility, and its open-source focus.

In this episode of Cloud Commute, Chris and Yingjun discuss:

• What is stream processing and how does it differ from batch processing?
• Why RisingWave is a better fit for real-time data analytics.
• How PostgreSQL compatibility enhances RisingWave’s functionality.
• What open standards like Postgres, Kafka, and Iceberg mean for the future of data infrastructure.

Interested to learn more about the cloud infrastructure stack like storage, security, and Kubernetes? Head to our website (https://podcasts.simplyblock.io/podcast/cloud-commute) for more episodes, and follow us on LinkedIn (www.linkedin.com/company/simplyblock-io/mycompany/). You can also check out the detailed show notes on Youtube (https://youtu.be/tJIoKWqInu4).

You can find Yingjun Wu (Founder & CEO at RisingWave Labs) on Linkedin: https://www.linkedin.com/in/yingjun-wu/

About simplyblock:

Simplyblock is an intelligent database storage orchestrator for IO-intensive workloads in Kubernetes, including databases and analytics solutions. It uses smart NVMe caching to speed up read I/O latency and queries. Single system connects local NVMe disks, GP3 volumes, and S3 making it easier to handle storage capacity and performance. With the benefits of thin provisioning, storage tiering, and volume pooling, your database workloads get better performance at lower cost without changes to existing AWS infrastructure.

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