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Graph in Kubernetes Panel (DoK Day EU 2022) // Wey Gu, Cheukting Ho & Feynman Zhou
Manage episode 329944577 series 2865115
https://go.dok.community/slack
From the DoK Day EU 2022 (https://youtu.be/Xi-h4XNd5tE)
Graph databases are the fastest growing data store in the world. According to Gartner, the application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science. However, it is often difficult for data and analytics professionals to distinguish between different implementation models, and to fit them to their use case. This panel will speak directly to Kubetnetes users and provide them with the context they need to run stateful workloads.
Topics for discussion would be:
- graph databases on Kubenetes challenges, lessons learnt, and patterns for deployment
- graph uses case on k8s, including scaling knowledge graphs
- K8s makes graph better
- technical patterns to use graph databases to get the maximum out of k8s
- the panels’ learnings from running graph data on Kubernetes
243 قسمت
Manage episode 329944577 series 2865115
https://go.dok.community/slack
From the DoK Day EU 2022 (https://youtu.be/Xi-h4XNd5tE)
Graph databases are the fastest growing data store in the world. According to Gartner, the application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science. However, it is often difficult for data and analytics professionals to distinguish between different implementation models, and to fit them to their use case. This panel will speak directly to Kubetnetes users and provide them with the context they need to run stateful workloads.
Topics for discussion would be:
- graph databases on Kubenetes challenges, lessons learnt, and patterns for deployment
- graph uses case on k8s, including scaling knowledge graphs
- K8s makes graph better
- technical patterns to use graph databases to get the maximum out of k8s
- the panels’ learnings from running graph data on Kubernetes
243 قسمت
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