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What is Vespa?

Vespa is designed for Big Data and AI, operating seamlessly online with unmatched efficiency, regardless of scale. It serves as a comprehensive search engine and vector database, enabling vector search (ANN), lexical search, and structured data queries all within a single request. The platform incorporates integrated machine-learning model inference, allowing users to leverage AI for real-time data interpretation. Developers often utilize Vespa to create recommendation systems that combine swift vector search capabilities with filtering and machine-learning model assessments for the items. To effectively build robust online applications that merge data with AI, it's essential to have more than just isolated solutions; you require a cohesive platform that unifies data processing and computing to ensure genuine scalability and reliability, while also preserving your innovative freedom—something that only Vespa accomplishes. With Vespa's established ability to scale and maintain high availability, it empowers users to develop search applications that are not just production-ready but also customizable to fit a wide array of features and requirements. This flexibility and power make Vespa an invaluable tool in the ever-evolving landscape of data-driven applications.

What is Milvus?

A robust vector database tailored for efficient similarity searches at scale, Milvus is both open-source and exceptionally fast. It enables the storage, indexing, and management of extensive embedding vectors generated by deep neural networks or other machine learning methodologies. With Milvus, users can establish large-scale similarity search services in less than a minute, thanks to its user-friendly and intuitive SDKs available for multiple programming languages. The database is optimized for performance on various hardware and incorporates advanced indexing algorithms that can accelerate retrieval speeds by up to 10 times. Over a thousand enterprises leverage Milvus across diverse applications, showcasing its versatility. Its architecture ensures high resilience and reliability by isolating individual components, which enhances operational stability. Furthermore, Milvus's distributed and high-throughput capabilities position it as an excellent option for managing large volumes of vector data. The cloud-native approach of Milvus effectively separates compute and storage, facilitating seamless scalability and resource utilization. This makes Milvus not just a database, but a comprehensive solution for organizations looking to optimize their data-driven processes.

Media

Media

Integrations Supported

IBM watsonx.data
AccessOwl
Coral
Kong AI Gateway
voyage-code-3

Integrations Supported

IBM watsonx.data
Amazon S3
Apache Kafka
Apache Pulsar
Azure Blob Storage
Cognee
Database Mart
Docker
Kubernetes
MinIO
Prompt Security
Zilliz Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Open source
Free Version
Free Trial Offered?

Pricing Information

Free
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Vespa.ai

Date Founded

2023

Company Location

Trondheim, Norway

Company Website

vespa.ai/

Company Facts

Organization Name

Zilliz

Date Founded

2020

Company Location

United States

Company Website

milvus.io

Categories and Features

AI Inference

Not specified

Context Engineering

Not specified

Neural Search

Not specified

Vector Databases

Not specified

Categories and Features

Context Engineering

Not specified

Database

Not specified

Vector Databases

Not specified

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