Momento Vector Index
Serverless vector indexing service designed for real-time storage and retrieval of vector data. Developer-friendly with just 5 API calls to create complete indexes, featuring transparent pricing. This is a commercial managed service.
About this tool
Overview
Momento Vector Index (MVI) is a scalable, developer-friendly, serverless vector index service for real-time storage and retrieval of vector data in AI-powered applications. Eliminates infrastructure management and scales automatically.
Key Features
- Serverless Architecture: No servers or infrastructure to manage
- Auto-Scaling: Automatically scales to meet demand
- Developer-Friendly: Create vector indexes with just 5 API calls
- Transparent Pricing: Pay only for what you use with no hidden fees
- Real-Time: Optimized for real-time vector retrieval
- Turnkey Solution: Complete vector store with minimal setup
Integration
LangChain Support
- Native integration with LangChain Python framework
- Turnkey serverless vector store for LangChain applications
- Seamless vector similarity search
API Access
- Simple REST API
- SDKs for .NET and Python
- Easy integration with existing applications
Use Cases
- AI chatbots with vector memory
- Semantic search applications
- Recommendation engines
- Anomaly detection systems
- Sentiment analysis
- RAG (Retrieval Augmented Generation)
Architecture
Designed for:
- High availability
- Low latency retrieval
- Automatic scaling without manual intervention
- No capacity planning required
Developer Experience
- Minimal API surface: just 5 calls to get started
- No complex configuration
- Focus on application logic, not infrastructure
- Quick time-to-production
Pricing Model
- Transparent: Clear pricing with no surprise costs
- Usage-Based: Pay only for actual usage
- Serverless: No idle capacity costs
- No Overpricing: Efficient cost structure
Contact Momento for detailed pricing information.
Availability
Announced at MoCon 2023, actively used in production by multiple organizations building AI applications.
Comparison to Traditional Solutions
- No infrastructure maintenance
- No capacity planning
- Automatic scaling
- Faster time to market
- Lower operational overhead
Loading more......
Information
Categories
Tags
Similar Products
6 result(s)Serverless Postgres with native pgvector support for vector embeddings and similarity search. Features instant provisioning, autoscaling, and scale-to-zero with separated compute and storage. This is a commercial managed service with free tier.
Serverless vector database with pay-per-use pricing and scale-to-zero capability. Fully managed service that scales to billions of vectors with simple per-request pricing. This is a commercial managed service.
Real-time analytics database with vector search capabilities, built on RocksDB with converged indexing. Acquired by OpenAI in 2024 to power retrieval infrastructure. This was a commercial service.
Managed vector database service with 1GB free forever cluster (no credit card required). Fully managed with multi-cloud support across AWS, GCP, and Azure. This is a commercial managed service.
Collaborative vector database platform described as 'GitHub for AI data'. Features distributed storage, HNSW indexing, and supports private, collaborative, and public vector datasets. This is a commercial platform with open collaboration features.
AI Search and RAG-as-a-Service platform with semantic search capabilities. Features NucliaDB open-source database. Acquired by Progress in 2025, now part of Progress Agentic RAG. This is a commercial service with OSS core (NucliaDB).