The use case: how Tinder deploys Elastic Cloud
Tinder uses Elasticsearch, hosted on Amazon EKS with Elastic Cloud on Kubernetes, for the retrieval stage of its recommendation pipeline, filtering tens of millions of profiles down to a small set of candidates based on location, preferences and profile signals. It adds custom optimizations such as geo-indexes, a Roaring bitmap exclusion filter and in-engine Java scoring of ML models.
More reported results
Figures published in Elastic Cloud’s case study. They are not independently measured by usedby.
Its system reduces feature extraction time by 84%, leading to 47% lower scoring latency during candidate ranking.
Additionally, Tinder boosted filtering performance by 60% through its use of Roaring bitmap technology to optimize large exclusion lists within Elasticsearch, meaning the system reduces the candidate pool sooner in the retrieval process.
In the customer’s words
You can think of it as a funnel. We start with the corpus of all the users, and then we narrow that down through several stages to the handful of recommendations that you see in the application.Other AI tools used by Tinder
Other public relationships recorded on usedby.
Explore Tinder’s AI stack
Other companies using Elastic Cloud
Customers across industries, with public evidence.
See all Elastic Cloud customers
Go straight to the source
Based on Elastic Cloud’s published case study. We check the public evidence; the results are reported by the vendor.
elastic.co- Last checked
- Nov 13, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 4xChecked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Tinder.
- Tinder uses Elastic CloudChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Tinder enhances retrieval by partitioning users into geo-indexes, meaning that Elasticsearch examines only nearby profiles instead of the entire global user base. As a result, Tinder dramatically reduces CPU usage and improves query latency while keeping recommendations highly relevant.