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Removed-Milvus

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Per Arun's request, removed the 2 mentions of Milvus
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Maddie Duhon
2025-03-07 09:08:40 -05:00
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qdrant-landing/content/blog/case-study-deutsche-telekom.md
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@@ -69,7 +69,7 @@ LMOS architecture powering AI agent collaboration and lifecycle management in a
### Why Qdrant? Finding the Right Vector Database for LMOS
When Deutsche Telekom began searching for a scalable, high-performance vector database, they faced operational challenges with their initial choice, Milvus. Seeking a solution better suited to their PaaS-first approach and multitenancy requirements, they evaluated alternatives, and [Qdrant](https://qdrant.tech/qdrant-vector-database/) quickly stood out.
When Deutsche Telekom began searching for a scalable, high-performance vector database, they faced operational challenges with their initial choice. Seeking a solution better suited to their PaaS-first approach and multitenancy requirements, they evaluated alternatives, and [Qdrant](https://qdrant.tech/qdrant-vector-database/) quickly stood out.
"I was looking for open-source components with deep technical expertise behind them," Arun recalls. "I looked at Qdrant and immediately loved the simplicity, [Rust-based efficiency](https://qdrant.tech/articles/why-rust/), and [memory management capabilities](https://qdrant.tech/articles/memory-consumption/). These guys knew what they were doing."
@@ -84,7 +84,7 @@ Deutsche Telekom's engineers also cited several standout features that made Qdra
2. **Developer experience**—libraries, multi-language clients, and cross-framework support make integrations seamless.
3. **WebUI & Collection Visualization**—engineers found Qdrant's [built-in collection visualization](https://qdrant.tech/documentation/web-ui/) tools highly useful.
As part of their evaluation, Deutsche Telekom engineers compared multiple solutions, weighing operational simplicity and reliability. One engineer summarized their findings: "Qdrant has way fewer components. Milvus required Kafka, Zookeeper, and only had a hot standby for its index and query nodes. If you rescale Milvus, you get downtime. Qdrant stays up."
As part of their evaluation, Deutsche Telekom engineers compared multiple solutions, weighing operational simplicity and reliability. One engineer summarized their findings: "Qdrant has way fewer components, compared to the previous solution that required required Kafka, Zookeeper, and only had a hot standby for its index and query nodes. If you rescaled it, you get downtime. Qdrant stays up."
### Scaling AI at Deutsche Telekom & The Future of LMOS