Paano Kalkulahin si Vector Database Cost

Ano ang Vector Database Cost?

The Vector Database Cost Calculator estimates monthly hosting expenses for vector storage and similarity search across managed services (Pinecone, Weaviate Cloud, Qdrant Cloud) and self-hosted options. It factors in vector dimensions, total vectors, query volume, and storage requirements.

Pormula

Monthly Cost = Base Plan Cost + (Vectors × Dimension × Bytes per Float × Storage Rate) + (Queries × Query Rate)

V: Number of Vectors (vectors) — Total stored vector embeddings
D: Dimensions (dimensions) — Dimensionality of each vector (768, 1024, 1536, 3072)
Q: Monthly Queries (queries/month) — Similarity search queries executed per month
QPS: Queries per Second (queries/sec) — Peak query throughput requirement

Step-by-Step na Gabay

1Enter the number of vectors and their dimensionality (768, 1024, 1536, 3072)
2Specify your monthly query volume and required queries per second (QPS)
3Select the vector database provider and deployment tier
4Compare costs across providers and self-hosted alternatives

Mga Nalutas na Halimbawa

Input

1M vectors at 1536 dimensions, 500K queries/month, Pinecone Serverless

Resulta

Storage: 1M × 1536 × 4 bytes = 6.14 GB. Pinecone Serverless: ~$70-$100/month for this workload. Weaviate Cloud: ~$65/month. Self-hosted Qdrant on $40/month VM: unlimited queries.

Input

10M vectors at 768 dimensions, 5M queries/month, high availability required

Resulta

Storage: ~30 GB. Pinecone Standard (s1 pod): ~$70/month base + scaling. Weaviate Enterprise: custom pricing. Self-hosted: 64GB RAM machine at ~$200/month.

Mga Karaniwang Mali na Dapat Iwasan

✕Over-dimensioning vectors — 768 or 1024 dimensions often perform nearly as well as 1536/3072 at much lower storage cost
✕Not planning for metadata storage, which can be 2-5x the size of the vectors themselves
✕Selecting a plan based on vector count alone without considering query throughput requirements

Mga madalas itanong

Which vector database is cheapest?

For small workloads (<100K vectors), most providers offer free tiers (Pinecone free tier: 100K vectors, Qdrant Cloud: 1GB free). For medium workloads, self-hosted Qdrant or Chroma on a $40-80/month VM is cheapest. For large-scale production, Pinecone Serverless offers competitive pay-as-you-go pricing.

Do I need a dedicated vector database or can I use PostgreSQL with pgvector?

For under 1M vectors with moderate query loads, pgvector in PostgreSQL is a solid and cost-effective choice, especially if you already run PostgreSQL. For >1M vectors, high QPS requirements, or features like automatic scaling and replication, dedicated vector databases outperform significantly.

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