Vercel has added Amazon S3 storage support to its marketplace, offering developers a streamlined way to manage storage resources. This integration includes S3 general purpose buckets, S3 Tables, and S3 Vectors, expanding Vercel’s existing AWS services like Amazon Aurora and DynamoDB.
Simplified Storage Management for Developers
Developers can now create and connect Amazon S3 resources directly within the Vercel dashboard, eliminating the need to switch to the AWS console. They select AWS under the storage tab, choose a bucket type and region, and attach it to a project. Vercel automatically injects essential environment variables, such as the AWS region and resource ARN, into the application environment.
The integration uses short-lived credentials for enhanced security, leveraging OpenID Connect token exchange with AWS Security Token Service to provide temporary access. This approach replaces long-term access keys, ensuring a more secure setup.
Targeted Workloads and Cost Efficiency
The new storage options cater to specific workloads. Standard S3 buckets store files like images, videos, and documents, supporting applications such as data lakes and mobile apps. S3 Tables focus on analytics, offering fully managed Apache Iceberg storage with automated maintenance. This service can be queried from engines like DuckDB that support the Iceberg REST catalog API.
For AI applications, S3 Vectors provides native vector storage and query functions, eliminating the need for a separate vector database. Amazon claims this service reduces the cost of uploading, storing, and querying vectors by up to 90%. Developers still generate embeddings using their own models, but the integration simplifies the overall workflow.
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Cost and Account Management
Amazon claims S3 Vectors can reduce vector storage and query costs by up to 90%. Developers can create a new AWS account or link an existing one. New accounts offer S3 features for testing, while linked accounts maintain current billing and access more AWS services.
There is no extra charge for the integration. Users pay standard Amazon S3 rates, and new AWS accounts created through Vercel get $100 in credits for six months.
Seamless Integration and Developer Experience
The integration keeps storage provisioning within the same workflow developers use to build and deploy applications on Vercel. Previously, teams manually configured AWS policies and credentials outside the Vercel environment. Now, developers can use the AWS SDK in a Next.js route to upload files to S3 buckets, list objects, and retrieve them.
For analytics, developers run DuckDB inside a Vercel function, attach an S3 Tables bucket by ARN, and execute SQL queries against Iceberg tables. In vector search, applications send an embedding to S3 Vectors and retrieve the closest matches from an index, supporting use cases like document search and AI assistants.
The services are accessible through v0, Vercel’s AI-assisted application-building tool. Users describe an application in natural language, and v0 automatically provisions the relevant S3 resource, configures the connection, and generates example code. Examples include a photo gallery using standard S3 storage, a support bot based on PDF files using S3 Vectors, and an analytics dashboard using S3 Tables.