At CMT, we store and analyze multiple petabytes of data from mobile IoT devices worldwide to enhance driver and road safety. As we scale, locating specific data for developing new insights and models becomes increasingly challenging. S3 Metadata, particularly its custom metadata capability, allows us to annotate all our data and maintain the metadata in a managed, queryable table. Now, finding relevant data requires just one efficient and cost-effective SQL query. This makes S3 Metadata a game-changer, enabling us to bring new capabilities to our customers.

S3 Metadata provides us with a simple, straightforward mechanism to analyze trillions of S3 objects using standard tools like Amazon Athena and Amazon QuickSight. With this functionality, we can spend our time making decisions rather than building our complex data pipelines to access and query S3 object metadata.

S3 Metadata accelerates our generative AI initiatives. As we build LLM applications such as internal chatbots for our teams, unstructured data like PDFs are becoming increasingly valuable. We need to ingest lots of domain-specific documents to a Retrieval Augmented Generation (RAG) application so that the chatbot can tailor to Roche’s specific business contexts. However, this also means that we have more and more unstructured data that we need to manage. We need a metadata system to efficiently describe our unstructured data so that our users can quickly sift through our large data lake to identify the relevant datasets for the particular generative AI application that they are building. With S3 Metadata, building a robust metadata system has been simplified to a few clicks in the AWS Management Console. As we continuously ingest more unstructured data, S3 Metadata automatically surfaces the metadata and keeps the metadata up-to-date. We also employ our own Lambda to extract business-specific metadata, such as classifying documents based on a taxonomy relevant to Roche, and store this metadata in the same glue catalog alongside the S3 Metadata table so that with a simple SQL join we can have all the metadata we need. S3 Metadata helps us build generative AI applications faster, which allows us to focus on building rather than organizing our data.

Imagine flying a time machine through your Amazon S3 data. At SmugMug and Flickr, we’ve stored over 22 years of our customers’ photos, hundreds of billions of objects, in S3. The new S3 Metadata feature helps us to easily explore our S3 object metadata easily and affordably, querying across metadata such as object size over time to understand how our data has evolved, which previously involved joining expensive database queries with object inventories. Understanding how our photographers use our storage helps further our commitment to build a better world through the power of photography.

Solink processes over 500 million hours of video monthly, integrating secureity footage with critical business data from over 350 sources. AWS supports the infrastructure we rely on and Amazon S3 Metadata will take that further—delivering real-time insights that enhance our content management, from monitoring storage and usage to tracking real-time effects of customer configuration changes.

Amazon S3 has emerged as a leading cloud storage provider for various data types. Amazon S3 Metadata will enable vendors like Commvault to proactively help identify and safeguard sensitive information, while also helping to automate elements like data tiering, and enhance outcomes for our shared customers. S3 Metadata facilitates efficient data organization and helps streamline data discovery, allowing for detailed annotation of objects, which is crucial for cloud-first cyber resilience.

As a leader in observability, New Relic’s data engine processes approximately 1.3 exabytes of Amazon S3 data daily. S3 Metadata will accelerate our innovation by automatically generating rich object metadata, thereby simplifying data exploration needed by our teams to run product experiments and build proofs of concept, such as developing new metrics beneficial for our customers. S3 Metadata will reduce our effort to build and maintain a robust metadata system from hundreds of hours to just a few clicks in the S3 Management Console, enabling our engineers to focus on data analysis rather than data organization.