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Index size is bounded by your infrastructure. The LMDB-backed index performs best when the working set fits in RAM. For very large datasets — tens of millions of documents with many text-heavy fields — Meilisearch becomes expensive to run because you need enough RAM to hold the hot index pages. The engine can handle datasets larger than RAM via memory-mapped I/O and OS page cache management, but query latency will degrade if the index doesn't fit. Elasticsearch's disk-based indexes handle this more gracefully at large scale.。关于这个话题，免实名服务器提供了深入分析
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