Databases · head to head
DuckDB vs Milvus

Milvus
Machine Learning
Open-source vector database for scalable similarity search
- From
- Free
- Rated
- -
The short version
- Each has a real cost: DuckDB client-server setup remains in beta and not recommended for production distributed scenarios; Milvus vector dimensions are capped at 32,768
- They diverge on capability: DuckDB covers In-process Execution, Milvus covers Billion-scale vectors.
Where they differ
Only the attributes on which DuckDB and Milvus actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in DuckDB
- In-process Execution
- Columnar Storage
- Vectorized Execution
- Rich SQL Support
- Parquet Support
- CSV/JSON Import
- Zero Dependencies
- Python
Only in Milvus
- Billion-scale vectors
- Multiple index types
- GPU acceleration
- Hybrid search
- Data partitioning
- PyTorch
- TensorFlow
- Hugging Face
Both cover
- Linux support
- Windows support
- Mac support
What people use each for
The jobs each tool is most often brought in to do.
DuckDB
- Analytics and data warehousingnot Milvus
- OLAP queries and data explorationnot Milvus
- Data science and machine learning workflowsnot Milvus
- Multi-format data ingestion and processingnot Milvus
Milvus
- Self hosting a vector database for semantic searchnot DuckDB
- Storing and querying embeddings for retrieval augmented generationnot DuckDB
- Similarity search over images, audio or text at scalenot DuckDB
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
DuckDB
- Client-server setup remains in beta and not recommended for production distributed scenarios
Milvus
- Vector dimensions are capped at 32,768
- A collection is limited to 64 fields, 1,024 partitions and 16 shards
- Only 1 index is allowed per field
- Search returns at most 16,384 vectors as top-k, and nq is capped at 16,384
- Input and output per RPC is capped at 64 MB for insert, search and query
- VARCHAR values are limited to 65,535 characters
- Data loaded into query nodes cannot exceed 90% of available memory
- An instance supports at most 65,536 collections
Pricing, plan by plan
DuckDB
FreeNo published plan breakdown. See the DuckDB review.
Milvus
Free- Open SourceFree
- Full features
- Self-hosted
- Community support
- Zilliz CloudFree
- Managed service
- Free tier available
Which should you pick?
Choose DuckDB if
- You need in-process execution.
- You want to start without paying.
- You work on Linux, macOS, Windows, WebAssembly.
- You also want columnar storage.
Choose Milvus if
- You need billion-scale vectors.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want multiple index types.
Questions people ask
- Is DuckDB or Milvus better?
- Neither clearly leads. DuckDB starts at Free and Milvus at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DuckDB or Milvus?
- DuckDB starts at Free and Milvus at Free.
- Does DuckDB or Milvus run on more platforms?
- DuckDB runs on Linux, macOS, Windows, WebAssembly. Milvus runs on Linux, Mac, Windows, Web.
- Can I use DuckDB for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is DuckDB best used for?
- DuckDB is most often used for analytics and data warehousing, olap queries and data exploration, data science and machine learning workflows, multi-format data ingestion and processing. Of those, analytics and data warehousing and olap queries and data exploration are not what Milvus is typically brought in for.
- What can DuckDB do that Milvus cannot?
- DuckDB covers In-process Execution, Columnar Storage, Vectorized Execution, Rich SQL Support. Milvus covers Billion-scale vectors, Multiple index types, GPU acceleration, Hybrid search. Both handle Linux support, Windows support, Mac support.
Answered from the vendors’ own pages
DuckDB: Is DuckDB free to use?
Yes, DuckDB is completely free. There are no subscription tiers, user limits, or paid plans. The software has zero licensing costs.
SourceMilvus: How much does Milvus cost?
Milvus is open-source and free to use and modify. The self-hosted version has no licensing cost. Zilliz Cloud (the managed SaaS version) does not publish pricing on the website.
SourceDuckDB: What license is DuckDB distributed under?
DuckDB is open source under the MIT License, governed by the independent DuckDB Foundation. The MIT License permits commercial use, modification, and distribution with minimal restrictions.
SourceMilvus: Is there a free or open-source version of Milvus?
Yes, Milvus is fully open-source and available for free. Milvus Lite is a lightweight option for learning and prototyping that can be installed via pip.
SourceDuckDB: Can I use DuckDB in commercial applications?
Yes, the MIT License allows commercial use without restrictions or requirements to publish proprietary code. You can deploy DuckDB anywhere from edge devices to high-core servers.
SourceMilvus: Does Milvus offer a managed cloud service?
Yes, Zilliz Cloud is a fully managed Milvus cloud offering with serverless and dedicated cluster options. Pricing must be requested from the company as it is not listed on the public website.
SourceDuckDB: Are there any limitations on how many instances I can run?
No, there are no user limits, usage limits, or instance restrictions. You have unlimited access to all DuckDB features.
SourceRelated pages
Other head to heads
- DuckDB vs Cockroach Labs
- DuckDB vs PostgreSQL
- DuckDB vs Airtable
- DuckDB vs Amazon Aurora
- DuckDB vs Elasticsearch
- DuckDB vs Apache Kafka
- DuckDB vs PlanetScale
- DuckDB vs Meilisearch
- DuckDB vs Turso
- DuckDB vs Azure SQL
- DuckDB vs ClickHouse
- DuckDB vs Couchbase
- DuckDB vs MariaDB
- DuckDB vs Oracle Database
- DuckDB vs DataGrip
- DuckDB vs Firebolt
- DuckDB vs Google Cloud SQL
- DuckDB vs MotherDuck
- DuckDB vs AWS SageMaker
- DuckDB vs Google Vertex AI
- DuckDB vs Azure Machine Learning
- DuckDB vs DataRobot
- DuckDB vs MLflow
- DuckDB vs Snowflake
- DuckDB vs TensorFlow
- DuckDB vs Comet ML
- DuckDB vs Jupyter
- DuckDB vs LangChain
- DuckDB vs Pinecone
- DuckDB vs Python
- DuckDB vs PyTorch
- DuckDB vs scikit-learn
- DuckDB vs Apache Spark MLlib
- DuckDB vs Weaviate
- DuckDB vs Weights & Biases
- DuckDB vs Alteryx
- Milvus vs Cockroach Labs
- Milvus vs PostgreSQL
- Milvus vs Airtable
- Milvus vs Amazon Aurora
- Milvus vs Elasticsearch
- Milvus vs Apache Kafka
- Milvus vs PlanetScale
- Milvus vs Meilisearch
- Milvus vs Turso
- Milvus vs Azure SQL
- Milvus vs ClickHouse
- Milvus vs Couchbase
- Milvus vs MariaDB
- Milvus vs Oracle Database
- Milvus vs DataGrip
- Milvus vs Firebolt
- Milvus vs Google Cloud SQL
- Milvus vs MotherDuck
- Milvus vs AWS SageMaker
- Milvus vs Google Vertex AI
- Milvus vs Azure Machine Learning
- Milvus vs DataRobot
- Milvus vs MLflow
- Milvus vs Snowflake
- Milvus vs TensorFlow
- Milvus vs Comet ML
- Milvus vs Jupyter
- Milvus vs LangChain
- Milvus vs Pinecone
- Milvus vs Python
- Milvus vs PyTorch
- Milvus vs scikit-learn
- Milvus vs Apache Spark MLlib
- Milvus vs Weaviate
- Milvus vs Weights & Biases
- Milvus vs Alteryx

