Running PostgreSQL and pgvector on Kubernetes: High-Performance AI Databases with Dell PowerFlex
May 14, 2026•Channel
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Video Overview
Video Details
Published1 month ago
Duration4:13
Video IDok2ZfPIvGz0
Languageen
CategoryScience & Technology
PrivacyPublic
Made for KidsNo
Video TypeRegular Video
Performance Metrics
Views35
Likes2
Comments0
Engagement Rate5.71%
Likes per 100 views5.71
Comments per 1K views0.00
Video Tags
#dell#technologies#dell technologies#postgresql#pgvector#postgresql on kubernetes#vector database#ai databases#semantic search#postgresql performance#dell powerflex#kubernetes storage#vector search postgresql#hnsw#ivf flat#rag pipelines#ai infrastructure#enterprise postgresql#database benchmarking#powerflex csi
Description
Enterprises want AI capabilities without adding new database platforms or operational complexity. In this video, we explore how PostgreSQL and the pgvector extension run on Kubernetes, backed by Dell PowerFlex, to support both OLTP workloads and high‑performance vector search in a single system.
Based on Dell Technologies White Paper H04651, this walkthrough highlights real benchmark results showing sub‑millisecond latency, over one million IOPS, and near‑linear scaling for PostgreSQL and pgvector workloads on Kubernetes.
You’ll see how pgvector enables vector embeddings, similarity search, and approximate nearest neighbor indexing using SQL, with a comparison of IVF‑Flat and HNSW indexing for AI workloads such as semantic search, recommendations, and RAG pipelines.
Topics covered:
* PostgreSQL on Kubernetes
* pgvector for vector search
* IVF‑Flat vs HNSW indexing
* Running OLTP and AI workloads together
* PowerFlex CSI for Kubernetes storage
* High‑performance database benchmarking
Download the full Dell Technologies white paper (H04651): https://infohub.delltechnologies.com/en-us/t/postgresql-and-vector-database-extension-on-dell-powerflex-with-kubernetes/
This video is ideal for database administrators, platform engineers, and architects looking to make PostgreSQL AI‑ready without introducing a separate vector database.