Qdrant
High-performance open-source vector DB
Overview
Qdrant is a high-performance open-source vector database written in Rust. Strong on filtering and metadata-aware search. Self-host free; managed Qdrant Cloud tier. Used by Mozilla, Disney+, Bayer.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 20 May 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
Use cases
ASEAN Perspective
Qdrant in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Qdrant is a leading open-source vector database written in Rust, widely used for retrieval-augmented generation, semantic search and recommendation. It offers excellent performance, advanced filtering, quantization for cost control, and both self-hosted and managed cloud options, with mature client SDKs across major languages. For engineering teams building AI search and RAG it is a top-tier, well-documented choice.
It is infrastructure rather than a turnkey app, so it assumes engineering competence to operate well at scale. The open-source core keeps value high (self-host for free), while Qdrant Cloud pricing is competitive. Cloud regions are global but ASEAN-local data residency may require self-hosting. A strong default for serious vector-search workloads.
About this listing
This entry was compiled from publicly available data including Qdrant's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Qdrant unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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