# DashVector

> Fully-managed, cloud-native vector search service from Alibaba Cloud based on the Proxima vector engine, offering horizontal scalability and instant vector updates for large-scale AI applications.

- **URL:** https://www.alibabacloud.com/en/product/dashvector
- **Category:** Managed Serverless Vector DBs
- **Tags:** Managed Service, Cloud Native, Scalable
- **Updated:** 2026-04-22 13:39
- **Canonical page:** https://vectordb.ever.works/he/items/dashvector

## Details

## Overview

DashVector is a fully-managed vector search service based on Proxima, an efficient vector engine developed by Alibaba's Tongyi Lab. The service provides cloud-native, horizontally scalable vector retrieval capabilities.

## Key Features

### Cloud-Native Architecture
- Fully managed on cloud infrastructure
- No server maintenance required
- Automatic scaling based on workload
- High availability and reliability

### Performance & Scalability
- Built on Proxima vector search engine
- Low-latency search on large-scale data
- Horizontal and vertical scaling capabilities
- Efficient vector retrieval algorithms
- Instant vector status updates

### Real-Time Indexing
- Flat index architecture supporting streaming data
- Online indexing from scratch
- Instant effect when vectors are added, deleted, or modified
- No rebuild required for updates
- Continuous data ingestion support

## Integration & API

### Simple APIs
- RESTful API for vector operations
- Python SDK available via PyPI (`pip install dashvector`)
- Easy integration with applications
- Comprehensive documentation

### Vector Management
- Insert, update, and delete operations
- Batch operations support
- Metadata filtering
- Multi-field indexing

## Use Cases

### E-Commerce
- Smart search based on product similarities
- Preference-based recommendations
- Visual search for products
- Personalized shopping experiences

### Large Language Models
- Semantic search for RAG applications
- Context retrieval for LLMs
- Knowledge base augmentation
- Question-answering systems

### Multi-Modal AI Search
- Text-to-image search
- Image-to-image similarity
- Cross-modal retrieval
- Video content search

### Scientific Applications
- Molecular structure analysis
- Drug discovery similarity search
- Protein structure comparison
- Chemical compound screening

### Media & Gallery
- Image similarity search
- Video content discovery
- Photo organization
- Content-based recommendations

## Technical Capabilities

### Proxima Engine
- High-performance vector indexing
- Advanced ANN algorithms
- Optimized for large-scale deployments
- Proven at Alibaba scale

### Data Management
- Support for various distance metrics
- Efficient storage optimization
- Automatic index management
- Built-in data persistence

### ModelScope Integration
- Vectorize multi-modal data using ModelScope models
- Open-source multi-modal embedding models
- Seamless model integration
- Pre-trained model support

## Deployment

### Alibaba Cloud Service
- Available through Alibaba Cloud console
- Pay-as-you-go pricing model
- Regional deployment options
- Enterprise support available

### SDK Installation
```bash
pip install dashvector
```

### Getting Started
1. Create DashVector instance on Alibaba Cloud
2. Obtain API credentials
3. Install SDK
4. Start indexing and searching vectors

## Performance Characteristics

- Low-latency queries on billion-scale datasets
- High QPS (Queries Per Second) capability
- Efficient memory utilization
- Optimized for production workloads

## Pricing

Managed service with consumption-based pricing through Alibaba Cloud. Costs vary based on:
- Number of vectors stored
- Query volume
- Instance size and configuration
- Data transfer

## Availability

Available globally through Alibaba Cloud regions with support for various compliance requirements and data residency needs.

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