PlanetScale Unveils Cloud-Native Database Built on Vitess

PlanetScale has announced the general availability of PlanetScale CNDb, a fully managed cloud-native database designed on Vitess, a Cloud Native Computing Foundation (CNCF)-hosted open source project that serves massive-scale production traffic at large web-scale companies such as YouTube, Slack, and Square.

Vitess is the eighth project to emerge, following Kubernetes, Prometheus, Envoy, CoreDNS, containerd, Fluentd, and Jaeger, from the CNCF.  To move from the maturity level of incubation to "graduation," projects must demonstrate thriving adoption, a documented, structured governance process, and a strong commitment to community, sustainability, and inclusivity.

PlanetScale was co-founded by CEO Jitendra Vaidya and CTO Sugu Sougoumarane, former YouTube engineers.

First created in 2010 as an internal solution at YouTube for scaling large amounts of storage using MySQL, Vitess is a cloud-native database system that delivers scale and flexibility. Vitess helps users migrate their stateful workloads to Kubernetes, scaling storage horizontally while presenting a MySQL-compatible interface to applications.

Gartner has projected that by 2022, 75% of all databases will be deployed or migrated to a cloud platform. According to PlanetScale,to address the growing cloud demand, infrastructure deployments of the future will be multi-cloud and will have built-in support for disaster recovery and data locality. PlanetScale’s database-as-a-service enables this multi-vendor, Kubernetes-powered future in the cloud, the company asserts.

PlanetScale CNDb is built on two key technologies: Vitess and MySQL. According to the company, with PlanetScale CNDb, as data grows, it is possible to scale up by splitting a database into more and more shards. In addition, PlanetScaleis vendor-agnostic, providing a platform that can host data on-prem and then seamlessly migrate it to the cloud provider of choice or a multi-cloud cluster if preferred. Finally, Vitess is designed from the ground up to provide guardrails and automations that allow organizations to scale their data without increasing the size of the database team.


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