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What is Seagate CORTX?

A design fostered by community collaboration allows for faster access to the latest innovations, while utilizing open source coding enables tailored customization to meet specific needs. Experience swift data retrieval with software capable of handling exabyte-scale, which significantly boosts both the efficiency and scalability of storage solutions. This system is meticulously optimized to support the increasing capacities of HDDs, guaranteeing data integrity and simplifying recovery efforts. You can now access CORTX, a thoroughly vetted and supported edition, bundled with our unified infrastructure offering, Lyve Drive™ Rack. With Lyve Drive Rack, we're revolutionizing enterprise storage by providing a holistic solution that merges up to 1.7PB of storage with CORTX object storage, delivering essential capacity without the burden of expensive software licensing fees. Enjoy scalability in performance without global locks across a variety of data types, including consistent object, key-value, file, and clusters. This methodology not only enriches your data experience but also organizes unstructured data, facilitating easy access, swift search functionalities, and effective analysis. Moreover, this groundbreaking solution is crafted to evolve alongside your business, ensuring you remain at the forefront of storage technology advancements while enhancing your overall operational efficiency. As your organization grows, you can trust that this flexible storage system will meet your future demands seamlessly.

What is Amazon S3 Vectors?

Amazon S3 Vectors stands out as a groundbreaking cloud object storage solution designed specifically for the large-scale storage and querying of vector embeddings, offering an efficient and economical option for applications like semantic search, AI-based agents, retrieval-augmented generation, and similarity searches. It introduces a unique “vector bucket” category within S3, allowing users to organize vectors into “vector indexes” and store high-dimensional embeddings that represent diverse forms of unstructured data, including text, images, and audio, while facilitating similarity queries through specialized APIs, all without requiring any infrastructure setup. Additionally, each vector can incorporate metadata such as tags, timestamps, and categories, which supports attribute-based filtered queries. One of the standout features of S3 Vectors is its remarkable scalability; it can manage up to 2 billion vectors per index and as many as 10,000 vector indexes within a single bucket, while ensuring elastic and durable storage accompanied by server-side encryption options through SSE-S3 or KMS. This innovative solution not only streamlines the management of extensive datasets but also significantly boosts the efficiency and effectiveness of data retrieval for developers and businesses, ultimately transforming the way organizations handle large volumes of unstructured data. With its advanced capabilities, Amazon S3 Vectors is positioned to redefine data storage and retrieval methodologies in the cloud.

Media

Media

Integrations Supported

Amazon S3
APERIO DataWise
GitHub
Stor2RRD
Swordfish
WEKA

Integrations Supported

Amazon S3
Amazon Bedrock
Amazon OpenSearch Service
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Mimasa AI

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Seagate

Company Location

United States

Company Website

www.seagate.com/products/storage/object-storage-software/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/s3/features/vectors/

Categories and Features

Object Storage

Not specified

Categories and Features

Object Storage

Not specified

Vector Databases

Not specified

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