Vector Search
Lakemeter UI name: Vector Search
Vector Search provides managed vector database endpoints for similarity search, powering RAG (Retrieval Augmented Generation) applications, recommendation systems, and semantic search. Lakemeter supports cost estimation for Standard and Storage-Optimized endpoint types.
The Vector Search guide — endpoint types, vector capacity calculation, and free storage tier explained.
Worked example showing CEILING-based unit calculation, DBU costs, and storage tier breakdown.
When to use Vector Search
Use Vector Search when you need a managed vector database for storing and querying embeddings -- things like RAG chatbots, document retrieval, product recommendations, or image similarity search. If you need to call a language model directly (not store embeddings), see FMAPI — Databricks Models instead.
Real-world example
Scenario: You are building a RAG-powered knowledge base on AWS us-east-1 (Premium tier). Your document corpus produces 10 million embeddings and you estimate 50 GB of associated metadata storage. You want a Standard endpoint running 24/7.
Configuration
| Field | Value |
|---|---|
| Workload Type | Vector Search |
| Endpoint Type | Standard |
| Capacity (Millions) | 10 |
| Storage (GB) | 50 |
| Hours Per Month | 730 (24/7) |
Step-by-step calculation
1. Compute units
Vector Search divides your vector capacity into fixed-size units. For Standard mode, each unit holds 2 million vectors:
Units = CEILING(Capacity in Vectors / Divisor)
= CEILING(10,000,000 / 2,000,000)
= CEILING(5)
= 5 units
2. DBU rate per hour
Each unit consumes 4.0 DBU/hour in Standard mode:
DBU/Hour = Units x DBU per Unit = 5 x 4.0 = 20.0 DBU/hour
3. Monthly compute cost
Monthly DBUs = DBU/Hour x Hours/Month = 20.0 x 730 = 14,600 DBUs
DBU Cost = 14,600 x $0.07/DBU = $1,022.00
4. Storage cost
Each unit includes 20 GB of free storage. Billing only applies to storage beyond this free tier:
Free Storage = Units x 20 GB = 5 x 20 = 100 GB
Billable = MAX(0, 50 - 100) = 0 GB (within free tier)
Storage Cost = $0.00
In this case, 50 GB is fully covered by the 100 GB free tier.
5. Total monthly cost
Total = DBU Cost + Storage Cost = $1,022.00 + $0.00 = $1,022.00/month
These are example rates for illustration. Actual $/DBU depends on your cloud, region, and pricing tier. Lakemeter loads real rates from the Databricks pricing bundle.
What about Storage-Optimized?
For the same 10 million vectors with Storage-Optimized:
Units = CEILING(10,000,000 / 64,000,000) = CEILING(0.15625) = 1 unit
DBU/Hour = 1 x 18.29 = 18.29 DBU/hour
Monthly = 18.29 x 730 = 13,351.7 DBUs
DBU Cost = 13,351.7 x $0.07 = $934.62
Storage-Optimized uses a much larger unit size (64M vectors vs 2M), so small deployments may actually cost more per unit but fewer units are needed. At 10M vectors, Standard and Storage-Optimized end up being close in cost.
Storage-Optimized becomes significantly cheaper at 100M+ vectors where the 64M divisor means far fewer units. For smaller deployments under 50M vectors, Standard is usually the better choice.
Endpoint types
| Type | Unit size | DBU/hr per unit | Best for |
|---|---|---|---|
| Standard | 2 million vectors | 4.0 | General RAG, moderate vector counts (< 100M) |
| Storage-Optimized | 64 million vectors | 18.29 | Large-scale search, 100M+ vectors, cost-sensitive storage |
How the CEILING function works
The number of compute units is always rounded up to the nearest whole number. This means:
- 1 vector → 1 unit (minimum)
- 2,000,001 vectors (Standard) → 2 units (crossed the 2M boundary)
- 63,999,999 vectors (Storage-Optimized) → 1 unit (still within 64M)
This is important for cost planning -- there is no "partial unit" pricing.
Configuration reference
| Field | Description | Default |
|---|---|---|
| Endpoint Type | Standard or Storage-Optimized. Determines unit size and DBU rate. | Standard |
| Capacity (Millions) | Number of vectors to store, in millions. | 1 |
| Storage (GB) | Metadata/additional storage in GB. Triggers a storage sub-row when it exceeds the free tier. | 0 |
| Hours Per Month | Service uptime. Use 730 for always-on endpoints. | 730 |
Free storage tier
Each compute unit includes free storage:
| Endpoint Type | Free storage per unit |
|---|---|
| Standard | 20 GB |
| Storage-Optimized | 20 GB |
Storage beyond the free tier is billed at $0.023/GB/month and appears as a separate sub-row in the Excel export.
How costs are calculated
Compute
Units = CEILING(Capacity Millions x 1,000,000 / Divisor)
DBU/Hour = Units x Mode DBU Rate
Monthly DBUs = DBU/Hour x Hours/Month
Compute Cost = Monthly DBUs x $/DBU
Where:
- Standard: Divisor = 2,000,000, DBU Rate = 4.0/hr per unit
- Storage-Optimized: Divisor = 64,000,000, DBU Rate = 18.29/hr per unit
Storage
Free Storage GB = Units x 20
Billable GB = MAX(0, Storage GB - Free Storage GB)
Storage Cost = Billable GB x $0.023/month
Total
Total = Compute Cost + Storage Cost
SKU mapping
| Component | SKU | Rate |
|---|---|---|
| Compute (all modes) | SERVERLESS_REAL_TIME_INFERENCE | $0.07/DBU (fallback) |
| Storage (over free tier) | Direct dollar amount | $0.023/GB/month |
Tips
- Right-size your capacity: Estimate the actual number of embeddings you will store. A typical RAG application with 10,000 documents (chunked into ~10 chunks each) needs ~100K vectors, not 100M. Enter capacity in millions.
- Account for the CEILING function: 2.1 million vectors costs the same as 4 million vectors in Standard mode (both need 2 units). Plan around unit boundaries to avoid paying for unused capacity.
- Storage-Optimized for large catalogs: If you have 100M+ product embeddings for e-commerce search, Storage-Optimized is significantly cheaper because each unit holds 64M vectors instead of 2M.
- Free storage covers many use cases: With 5 Standard units (10M vectors), you get 100 GB free storage. Most RAG metadata fits within the free tier.
Common mistakes
- Confusing millions with actual vector count: The Capacity field is in millions. If you have 5 million vectors, enter 5, not 5,000,000.
- Ignoring the unit rounding: Going from 2M to 2.1M vectors in Standard mode doubles your cost (1 unit → 2 units). Be aware of the unit boundaries.
- Choosing Storage-Optimized for small deployments: At less than 10M vectors, Standard is almost always cheaper because the minimum is 1 unit either way, and Standard's per-unit DBU rate is lower.
- Expecting VM costs: Vector Search is always serverless. $0 VM cost is correct.
Excel export
Vector Search workloads may export as one or two rows:
| Row | When | Contents |
|---|---|---|
| Compute row | Always | DBU-based cost for the endpoint units |
| Storage sub-row | When storage exceeds free tier | Dollar-based storage cost ($0.023/GB/month for billable GB) |
| Column (compute row) | What it shows |
|---|---|
| Configuration | Endpoint type and capacity |
| Mode | Serverless (always) |
| SKU | SERVERLESS_REAL_TIME_INFERENCE |
| DBU/Hour | Units x mode DBU rate |
| Hours/Month | Direct value |
| Monthly DBUs | DBU/Hour x Hours/Month |
| DBU Cost | Monthly DBUs x $/DBU |
| VM Cost | $0 (always serverless) |
| Total Cost | DBU Cost + Storage Cost |