Zilliz Cloud vs Qdrant
- ✦ Distributed Architecture
- ✦ Billion-Scale Vectors
- ✦ ANNS Algorithms (HNSW, IVF, DiskANN)
- ✦ Written in Rust
- ✦ HNSW Index
- ✦ Sparse Vectors (BM25-compatible)
Zilliz Cloud and Qdrant are both Vector Databases tools. Zilliz Cloud starts at $126/mo, Qdrant at $65/mo. Compare features, pricing, and ratings below to find the best fit for your team.
When to Choose Zilliz Cloud vs Qdrant
The question that matters: “In what situation will I regret choosing A over B after 3 months?”
Milvus scales to trillions of vectors using hierarchical index structures with tiered storage, serving billion-scale collections that exceed single-machine memory limits via Zilliz Cloud managed deployment.
Qdrant's HNSW indexes integrate payload filtering natively, executing filtered nearest-neighbor search without a post-filter scan step, maintaining sub-50ms latency on complex metadata filters.
Milvus GPU indexing builds IVFPQ indexes on billion-vector collections 10x faster than CPU-only builds, reducing the time from ingestion to searchable index for large-scale embedding pipelines.
Qdrant's on-disk HNSW stores vectors on SSD while keeping only graph navigation data in RAM, serving collections larger than server memory at acceptable latency for cost-sensitive deployments.
Milvus partitions split a collection by tenant key, improving query isolation and allowing partition-level operations like load/release to balance memory usage across a shared cluster.
Qdrant supports sparse vectors natively alongside dense vectors, enabling BM25 and embedding search in the same collection for hybrid retrieval without maintaining two separate indexes.
Pricing Comparison & PlansHigh· Verified Jul 8, 2026
Zilliz Cloud Plans
Free tier available
Free
FreeBest for: Learning & personal projects
- ✓5 GB storage
- ✓2.5M vCUs/mo included
- ✓Up to 5 collections
- ✓Serverless
Standard (Dedicated)
from $126/GB/moBest for: Prototypes & testing (non-critical)
- ✓From $0/mo serverless OR $126/GB-mo dedicated
- ✓Fully managed core APIs
- ✓Backup & restore
- ✓Basic monitoring
- ✓Encryption in transit + at rest
Enterprise (Dedicated)
from $197/moBest for: Production applications
- ✓99.95% uptime SLA
- ✓Audit logs
- ✓SSO (SAML 2.0)
- ✓Granular RBAC
- ✓Multi-replica + elastic scaling
Business Critical
Contact SalesBest for: Healthcare / finance / regulated mission-critical
- ✓Global cluster HA + DR
- ✓CMEK + full-path encryption
- ✓HIPAA-eligible
- ✓Priority support
Qdrant Plans
Free tier available
Open Source (Self-Hosted)
Open SourceBest for: Ideal for users who prefer full control and self management of their vector database
- ✓Apache 2.0 licensed
- ✓Full data sovereignty
- ✓Runs on your own infrastructure
- ✓Zero licensing cost at any scale
Free Tier
FreeBest for: Testing and prototypes
- ✓Single Node Cluster
- ✓Free Cloud Inference with selected models
- ✓Ideal for testing and prototypes
Standard
$65/moBest for: Production workloads + scaling
- ✓Production workloads
- ✓Dedicated clusters
- ✓Higher availability
- ✓Automated daily backups
- ✓Built-in monitoring and alerting
Capability Breakdown
1 differences found across 14 standardized features
- •Open Source (Apache 2.0)
- •Distributed Architecture
- •Billion-Scale Vectors
- •ANNS Algorithms (HNSW, IVF, DiskANN)
- •Hybrid Search
- •GPU Acceleration
- •Multi-vector Search
- •Sparse Vector Support
- •Metadata Filtering
- •Data Partitioning
- •Incremental Indexing
- •Python/Java/Go SDKs
- •Kubernetes Native
- •LangChain Integration
- •Time Travel (data versioning)
- •RBAC
- •Open Source (Apache 2.0)
- •Written in Rust
- •HNSW Index
- •Sparse Vectors (BM25-compatible)
- •Multi-vector Support
- •Payload Filtering
- •Full-Text Search
- •Named Vectors
- •Quantization (Scalar, Product, Binary)
- •Distributed Mode
- •Snapshot & Recovery
- •REST & gRPC APIs
- •Python/JS/Rust/Go SDKs
- •LangChain Integration
- •On-Premise + Cloud
- •Web UI Dashboard
Strengths & Limitations
Evaluative strengths and weaknesses: not feature lists
- +CNCF project: battle-tested for billion-scale workloads
- +GPU acceleration and DiskANN for cost-efficient large-scale search
- +Distributed architecture with independent storage/compute scaling
- +Multi-vector search supports complex AI use cases
- −Operational complexity: requires Kubernetes expertise for self-hosted
- −Overkill for small-scale RAG applications
- +Top benchmark performance via Rust and quantization
- +Named vectors enable multimodal and complex search patterns
- +Binary quantization reduces memory 32x
- +Excellent documentation and developer experience
- −The area for improvement in Qdrant is its clustering capability.
At a Glance
Recent Price History
Zilliz Cloud added a new "Standard (Dedicated)" plan at $126/GB/mo
Plan added · Jul 6, 2026
Zilliz Cloud added a new "Enterprise (Dedicated)" plan at $197/mo
Plan added · Jul 6, 2026
Zilliz Cloud added a new "On-demand Compute" plan (Custom pricing)
Plan added · Jul 6, 2026
Zilliz Cloud removed the "Serverless" plan
Plan removed · Jul 6, 2026
Zilliz Cloud removed the "Dedicated Business Critical" plan
Plan removed · Jul 6, 2026
Qdrant removed the "Cloud Standard" plan
Plan removed · May 30, 2026
Qdrant removed the "Open Source" plan
Plan removed · May 30, 2026
Qdrant added a new "Free Tier" plan at $0/mo (Free)
Plan added · May 30, 2026
Qdrant added a new "Standard" plan at $65/mo
Plan added · May 30, 2026
Qdrant removed the "Enterprise" plan
Plan removed · May 30, 2026
Frequently Asked Questions
Related Comparisons
Zilliz CloudFree · from $126/mo
QdrantFree · from $65/moSources & Data Trail · Zilliz Cloud
- 1.Official Pricing Page·Source of verified tiers(Checked: 2026-07-08)
- 2.Official Website·Official vendor website
- 3.G2·G2 verified reviews · 4.4/5 · 53 reviews
Sources & Data Trail · Qdrant
- 1.Official Pricing Page·Source of verified tiers(Checked: 2026-07-08)
- 2.Official Website·Official vendor website
- 3.G2·G2 verified reviews · 4.5/5 · 12 reviews
- 4.PeerSpot·PeerSpot enterprise peer reviews