Batch write and discover records in Amazon SageMaker Feature Store
Amazon Web Services Harshil Shah
AWS SageMaker Feature Store got two new APIs: one writes up to 25 records at once, the other lists record IDs. That fixes slow batch writes and the “lost ID, lost data” problem for the In-Memory tier.
Based on reporting by Amazon Web Services, Harshil Shah — read the original for the full story.
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Amazon is adding two long-missing tools to SageMaker Feature Store: BatchWriteRecord and ListRecords. One tackles ingestion bottlenecks. The other tackles a simpler, nastier problem — what happens when you know data exists, but you can’t find the record IDs for it anymore.
BatchWriteRecord lets teams send up to 25 records in a single call, even across multiple feature groups. That matters because the existing PutRecord flow writes one record at a time, which turns high-throughput pipelines into a thicket of repeated API calls. AWS says a fraud pipeline pushing 10,000 records a second across five feature groups would need 50,000 calls a second just to keep up.
The new API keeps the same EventTime-based ordering rules as PutRecord. If a record is newer, it becomes the latest version in the online store. If it is stale, it still lands as a historical version in the offline store, where that store exists. And because BatchWriteRecord is partial-success, one bad record doesn’t poison the rest of the request. Failed entries come back in Errors, while anything left unprocessed is returned separately so you can retry only those rows.
AWS is also letting each entry aim at OnlineStore, OfflineStore, or both, with TTL control at the record level, the request level, or the feature-group level. The limit is still 25 entries per request, and authorization is checked per feature group before processing. So this is not a giant new abstraction. It is a cleaner way to do the same work without making the network do all the sweating.
ListRecords fills the discovery gap. Feature Store already had PutRecord, GetRecord, and DeleteRecord, but they all assume you already know the identifier. Now you can page through active, non-deleted, non-expired records in both Standard and In-Memory feature groups. For the Redis-backed tier, that is a real fix: if record identifiers disappear, the data was previously just sitting there, unrecoverable and annoying in equal measure.
My take — AI-written commentary, not fact-checked reporting
This is the kind of boring infrastructure work that actually earns its keep. Batch writes save people from building their own mini-queue of shame, and ListRecords finally admits that “just know the ID” is not a strategy. The industry spends a lot of time talking about smarter models; sometimes the smarter move is making the storage layer less stupid.
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