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title: Azure Cosmos DB Migration Guide for Elasticsearch Users
description: Microsoft outlines a migration path for teams moving Elasticsearch-backed search workloads to Azure Cosmos DB, contrasting the architectures: Elasticsearch...
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# Azure Cosmos DB Migration Guide for Elasticsearch Users

**[DevBlogs](https://daily.dev/sources/devblogs)** · 3 min read · 0 upvotes · 0 comments

## Summary

Microsoft outlines a migration path for teams moving Elasticsearch-backed search workloads to Azure Cosmos DB, contrasting the architectures: Elasticsearch uses a separate synchronized search cluster, while Cosmos DB integrates full-text, vector, and hybrid search directly into the operational database. The guide maps common Elasticsearch features to Cosmos DB equivalents (multilingual search in preview, fuzzy search, hybrid search, faceting, pagination), notes that weighted BM25 is still in development, and flags gaps like synonym management, proximity search, advanced autocomplete, and built-in hit highlighting that aren't yet natively supported. It's the first in a three-part series, with future posts covering mapping translation and query translation.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-migration-guide-for-elasticsearch-users>

## Questions this post answers

### What Elasticsearch search features are not currently supported natively in Azure Cosmos DB?

Synonym management, proximity search, advanced autocomplete, and built-in hit highlighting are not currently available natively in Azure Cosmos DB and require application-side implementation. Multilingual full-text search is supported but currently in preview, and weighted BM25 scoring is still in development, so teams migrating from Elasticsearch need to plan workarounds for these gaps.

_Track which Elasticsearch features still need workarounds in Cosmos DB by following coverage of this migration on daily.dev._

### How does Azure Cosmos DB's search architecture differ from Elasticsearch's?

Elasticsearch typically runs as a separate search cluster, requiring data to be copied, indexed, and kept synchronized with the operational database. Azure Cosmos DB instead provides full-text, vector, and hybrid search directly over the operational data within the same service, removing the synchronization layer but requiring search to be designed alongside partitioning, indexing, and request-unit usage.

_Compare database and search architecture trade-offs like these on daily.dev before committing to a migration._

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---

Tags: [#database](https://daily.dev/tags/database), [#elk](https://daily.dev/tags/elk), [#nosql](https://daily.dev/tags/nosql), [#full-text-search](https://daily.dev/tags/full-text-search), [#azure-cosmos-db](https://daily.dev/tags/azure-cosmos-db)

[View this post on daily.dev](https://daily.dev/posts/azure-cosmos-db-migration-guide-for-elasticsearch-users-6r3julzco)

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