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Reading: How DoorDash Optimized Item Availability at Scale Using Elasticsearch | HackerNoon
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World of Software > Computing > How DoorDash Optimized Item Availability at Scale Using Elasticsearch | HackerNoon
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How DoorDash Optimized Item Availability at Scale Using Elasticsearch | HackerNoon

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Last updated: 2026/04/10 at 9:51 AM
News Room Published 10 April 2026
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How DoorDash Optimized Item Availability at Scale Using Elasticsearch | HackerNoon
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DoorDash’s homepage item carousels needed to filter millions of items by availability in under 300ms. We couldn’t call the menu service at request time (too much fan-out, too slow), so we indexed availability directly in Elasticsearch. We went through three schema iterations: nested documents (600ms), Gojek-style encoded time slots as terms (350ms but 6x storage), and finally range fields backed by BKD trees (250ms, baseline storage). The range approach won on both latency and storage.

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