Qdrant vs Milvus
Both are alternatives to Pinecone. Here's how they stack up — verified facts, no spin.
Also searched as Milvus vs Qdrant — same comparison, one verdict.
Qdrant keeps your data local by default and Milvus keeps it in the vendor's cloud — for most teams that single fact decides it.
Qdrant
TOP PICKFast, open-source, one binary — the default self-hosted vector DB.
Qdrant is a high-performance vector database written in Rust and licensed Apache-2.0 — free to self-host with no usage limits or feature gates. It ships as a single self-contained binary with REST and gRPC APIs, runs via Docker or Kubernetes (official Helm chart and Operator), and offers a managed Qdrant Cloud on AWS, GCP, and Azure when you'd rather not operate it. Strong filtering, quantization, and hybrid search make it the most common 'we left Pinecone' landing spot.
Milvus
The heavy-scale distributed choice — billions of vectors, Apache-2.0.
Milvus is a cloud-native, distributed vector database under the LF AI & Data Foundation, licensed Apache-2.0 and developed by Zilliz. It is engineered for the top end of scale — billions of vectors, horizontal scaling, tiered storage — with a managed option (Zilliz Cloud) when you want the same engine without the Kubernetes homework. If your vector workload is genuinely huge, this is the open-source engine built for it.
Side by side
10 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| Qdrant | Milvus | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 92 | 88 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first data | Yes | No |
| License | Apache-2.0 | Apache-2.0 |
| Pricing | Free self-hosted (no limits); Qdrant Cloud managed tiers with a free 1GB cluster | Free self-hosted (Apache-2.0); Zilliz Cloud managed tiers incl. a free tier |
| RAM to run it wellThe figure that actually matters, not the vendor's minimum. | Vectors × dimensions × 4 bytes, in RAM, plus overhead — 1M × 768d is roughly 3 GB | — |
| Realistic running costWhat the box costs each month if you run it yourself. | $25–60/mo for a few million vectors, against Pinecone's $50/mo floor plus usage | — |
| Setup timeHonest first-install estimate, not the marketing quickstart. | 30 minutes | — |
| Ongoing maintenanceThe part nobody budgets for. | Low. Snapshots for backup, and watch memory as the collection grows. | — |
Qdrant is Macrostack's recommended Pinecone alternative, so it's our pick here.
Weighing both against staying on Pinecone? Is Pinecone free? What it actually costs →
Qdrant
Strengths
- +Apache-2.0, no feature gates — the full engine is open
- +Single Rust binary: laptop to cluster with the same API
- +Excellent metadata filtering, quantization, hybrid search
- +Managed cloud exists when you want zero ops
Trade-offs
- −Self-hosting means you own scaling and backups
- −Smaller managed-service ecosystem than Pinecone's
Milvus
Strengths
- +Proven at billion-vector scale, horizontally scalable
- +LF AI & Data governance — not a single-vendor project
- +Managed escape hatch (Zilliz Cloud) with the same engine
Trade-offs
- −Distributed architecture = real operational complexity self-hosted
- −Overkill for small and mid-size workloads
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose Qdrant
if your data should stay on machines you control, and apache-2.0, no feature gates — the full engine is open.
Choose Milvus
if proven at billion-vector scale, horizontally scalable.
Neither, yet
if both carry a real cost you should weigh first — self-hosting means you own scaling and backups, and distributed architecture = real operational complexity self-hosted. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
What it takes to run these yourself
Real requirements and honest running costs, not the vendor quickstart.
Qdrant vs Milvus — common questions
Is Qdrant a better fit than Milvus for vector databases & ai search?
It depends on what you are optimising for, and the honest split is this: Qdrant scores 92 to Milvus's 88 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. Milvus earns its place on a different axis — proven at billion-vector scale, horizontally scalable. Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
Qdrant keeps its data local or in open formats, so leaving is an export rather than a negotiation. Milvus is still self-hostable, so the files stay on your server either way — but it is not local-first by design, so check what its export produces before you rely on it.
Can I self-host Qdrant or Milvus?
Both can be self-hosted. The difference is what it costs you in time rather than whether it is possible — see the setup and maintenance rows above.
Are Qdrant and Milvus both alternatives to Pinecone?
Yes — both appear in our Pinecone comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off Pinecone and now choosing between the two replacements, which is a narrower and much easier question.
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Facts verified 2026-07-15. Licenses and pricing change — spotted something out of date? That's a correction we want.