Skip to main content

Azure Cosmos DB developer hub

Build with Azure Cosmos DB

Build apps and AI agents on a globally distributed database. SDKs, tools and samples, plus the community and training to go with them.

Start buildingPython quickstart (opens in new tab)

Give an AI agent a memory: store it, then recall it by meaning.

pip install azure-cosmos
# container has a vector index on /embedding
# embed() calls your embedding model
container.upsert_item({
    "id": "m1",
    "userId": "ava",
    "text": "Prefers window seats",
    "embedding": embed("Prefers window seats"),
})


hits = container.query_items(
    query="SELECT TOP 3 c.text, VectorDistance(c.embedding, @q) AS score "
          "FROM c ORDER BY VectorDistance(c.embedding, @q)",
    parameters=[{"name": "@q", "value": embed("Where should Ava sit?")}],
    partition_key="ava",
)
dotnet add package Microsoft.Azure.Cosmos
// container has a vector index on /embedding
// Embed() calls your embedding model
PartitionKey pk = new("ava");
await container.UpsertItemAsync(
    new Memory("m1", "ava", "Prefers window seats", Embed("Prefers window seats")), pk);


QueryDefinition query = new QueryDefinition(
        "SELECT TOP 3 c.text, VectorDistance(c.embedding, @q) AS score " +
        "FROM c ORDER BY VectorDistance(c.embedding, @q)")
    .WithParameter("@q", Embed("Where should Ava sit?"));


using FeedIterator<MemoryHit> hits = container.GetItemQueryIterator<MemoryHit>(
    query, requestOptions: new QueryRequestOptions { PartitionKey = pk });


record Memory(string id, string userId, string text, float[] embedding);
record MemoryHit(string text, double score);
com.azure:azure-cosmos (Maven / Gradle)
// container has a vector index on /embedding
// embed() calls your embedding model
container.upsertItem(
    new Memory("m1", "ava", "Prefers window seats", embed("Prefers window seats")));


SqlQuerySpec query = new SqlQuerySpec(
    "SELECT TOP 3 c.text, VectorDistance(c.embedding, @q) AS score "
        + "FROM c ORDER BY VectorDistance(c.embedding, @q)",
    new SqlParameter("@q", embed("Where should Ava sit?")));


CosmosPagedIterable<MemoryHit> hits = container.queryItems(
    query,
    new CosmosQueryRequestOptions().setPartitionKey(new PartitionKey("ava")),
    MemoryHit.class);
npm install @azure/cosmos
// container has a vector index on /embedding
// embed() calls your embedding model
await container.items.upsert({
  id: "m1",
  userId: "ava",
  text: "Prefers window seats",
  embedding: await embed("Prefers window seats"),
});


const { resources: hits } = await container.items
  .query(
    {
      query:
        "SELECT TOP 3 c.text, VectorDistance(c.embedding, @q) AS score " +
        "FROM c ORDER BY VectorDistance(c.embedding, @q)",
      parameters: [{ name: "@q", value: await embed("Where should Ava sit?") }],
    },
    { partitionKey: "ava" },
  )
  .fetchAll();
go get github.com/Azure/azure-sdk-for-go/sdk/data/azcosmos
// container has a vector index on /embedding
// embed() calls your embedding model
// error handling omitted for brevity
pk := azcosmos.NewPartitionKeyString("ava")
body, _ := json.Marshal(map[string]any{
    "id": "m1", "userId": "ava", "text": "Prefers window seats",
    "embedding": embed("Prefers window seats"),
})
_, _ = container.UpsertItem(ctx, pk, body, nil)


pager := container.NewQueryItemsPager(
    "SELECT TOP 3 c.text, VectorDistance(c.embedding, @q) AS score "+
        "FROM c ORDER BY VectorDistance(c.embedding, @q)",
    pk,
    &azcosmos.QueryOptions{QueryParameters: []azcosmos.QueryParameter{
        {Name: "@q", Value: embed("Where should Ava sit?")}, // []float64
    }},
)
cargo add azure_data_cosmos futures
// container has a vector index on /embedding
// embed() calls your embedding model
let memory = Memory {
    id: "m1".into(),
    user_id: "ava".into(),
    text: "Prefers window seats".into(),
    embedding: embed("Prefers window seats"),
};
container.upsert_item("ava", "m1", memory, None).await?;


let query = Query::from(
    "SELECT TOP 3 c.text, VectorDistance(c.embedding, @q) AS score \
     FROM c ORDER BY VectorDistance(c.embedding, @q)",
)
.with_parameter("@q", embed("Where should Ava sit?"))?;


let mut hits = container
    .query_items::<MemoryHit>(query, FeedScope::partition("ava"), None)
    .await?;
while let Some(hit) = hits.try_next().await? {
    println!("{} ({})", hit.text, hit.score);
}

Develop

Pick your language to see its quickstart, SDK guide and API reference.

Developer guide

Get started with Python

Install the SDK, connect to your account and run your first query.

Data modeling & partitioning

Shape your data and pick a partition key that scales.

Queries & change feed

Read your data back and react to every change.

Vector search & AI

Build retrieval and agent memory on your operational data.

Performance & cost

Understand request units and tune for throughput.

Consistency & global distribution

Trade latency, availability and consistency on purpose.

What will you create?

Start with a real scenario. Find the code, learn the pattern, and make it your own.

Looking for working code? Start from a ready-made sample.Browse the sample gallery (opens in new tab)

Learn

From your first query to a credential you can show: watch it, read it, build with it, get certified.

New to Azure Cosmos DB? Start small. Run your first NoSQL queries.Try the introductory module on AI Skills Navigator (opens in new tab)

Get certified

DP-420AI-focused / Updated October 2026

Build confidence. Prove your skills.

Azure Cosmos DB AI Developer Associate

Design, build, and optimize scalable AI applications with Azure Cosmos DB. Bring your database fundamentals together with RAG, agent memory, and conversation state.

Explore the certification (opens in new tab)

Microsoft Certified: Azure Cosmos DB AI Developer Associate.

Your learning launchpad

A clear path from curious to ready.

Start with a short module, follow the full course, or work through a learning path.

  1. New here? Try Azure Cosmos DB.Introductory module / Get hands-on with the basics (opens in new tab)
  2. Build AI applications with Azure Cosmos DB.DP-420 course / Follow the full learning journey (opens in new tab)
  3. Develop AI solutions with Azure Cosmos DB.Learning path / Put AI capabilities into practice (opens in new tab)

Current study guide (opens in new tab)Practice & exam scheduling on Learn (opens in new tab)

Take DP-420 for less

Microsoft Ignite / In person

November 17-20, 2026 / San Francisco

Ignite is your launchpad.

Meet the developer community, explore Azure Cosmos DB sessions, and take DP-420 onsite at no charge if you're a registered in-person attendee.

Testing: November 16-20. One Microsoft or one GitHub exam per eligible attendee. Registration, available seats, and official terms apply.

Explore onsite certification (opens in new tab)

Data Days: AI @ Work / Online

50% exam discount request opportunity

Keep the momentum going, wherever you are.

DP-420 is included in the Data Days certification offer. Join Fabric Community, watch two Data Days sessions, then submit a discount request.

November 2-December 15. Request by December 10, 2026, while supplies last. Eligibility and offer terms apply; issuance is not guaranteed. Offer terms (opens in new tab)

Explore Data Days (opens in new tab)

From the blog

  • ChatGPT runs on Azure Cosmos DB. Prove you can build what’s next.

    Take the newly AI-focused DP-420 exam free at Microsoft Ignite—or take the certification exam today and save 50% through Data Days.

    Read the article (opens in new tab)

  • My Team Is Growing, How Do I Structure Who Gets Access to What?

    Your project started with one or two people. Now developers, operators, analysts, and applications all need access to Azure Cosmos DB.

    Read the article (opens in new tab)

  • Agentic CI/CD with Azure Cosmos DB: Isolated Environments for a Swarm of AI Agents

    Give each coding task its own disposable database environment, then merge the reviewed changes – not the test database.

    Read the article (opens in new tab)

  • Inspecting Local Data with Azure Cosmos DB Shell

    Explore local data from the terminal with Azure Cosmos DB Shell. Connect to the emulator, inspect FleetCharge documents, run queries, and point-read depot partitions.

    Read the article (opens in new tab)

  • Code with Cosmos: Build a Production-Ready AI App in Four Episodes

    Follow an AI application from a blank folder to a system built for production AI application development often starts with a promising prototype.

    Read the article (opens in new tab)

  • From Local Development to CI Workflows with the Azure Cosmos DB Emulator

    When you change a database-backed feature, a successful HTTP response isn’t enough. You need to know that the write reached storage, the application retrieved the updated record, and the next answer reflects it.

    Read the article (opens in new tab)

  • Announcing GA of Safe Key Rotation in Azure Cosmos DB

    In our previous post, we introduced the private preview of Safe Key Rotation, a feature that helps Azure Cosmos DB customers avoid service disruptions during key rotations.

    Read the article (opens in new tab)

  • AI Agents: Meet the Azure Cosmos DB vNext Emulator

    Over a typical 2 day window, we record 10 times as many emulator sessions lasting more than 30 minutes for vNext as for the legacy emulator. Our bet is that agentic development is helping drive the difference!

    Read the article (opens in new tab)

  • Introducing the Native Confluent Cloud Connector Experience in Azure Cosmos DB!

    Co-authored with Praveen Raja P Azure Cosmos DB already includes a powerful event foundation: change feed provides a durable, ordered record of item changes within each logical partition.

    Read the article (opens in new tab)

Read the Azure Cosmos DB blog (opens in new tab)

Tools

Everything around the SDK: write and debug in your editor, let AI assistants work with your data, and plan and migrate your workload.

Build & debug

Write, run and inspect your data from the editor, the browser or your laptop.

AI-assisted development

Let coding assistants and agents work with Azure Cosmos DB, with the right guardrails.

Plan & migrate

Size your workload, then move your data in.

Community

Ask a question. Share a build. Join a conversation. Choose the community that works for you.

Microsoft Open Source DiscordConnect in the wider Microsoft developer community. Not a Cosmos-only server. (opens in new tab)r/CosmosDBTalk with other Azure Cosmos DB users in an independently moderated community. (opens in new tab)GitHubFind SDKs, samples, workshops and places to contribute to the Cosmos ecosystem. (opens in new tab)Microsoft Q&AAsk a technical question or browse answers under the Azure Cosmos DB tag. (opens in new tab)XFollow @AzureCosmosDB. (opens in new tab)LinkedInNews from the product team. (opens in new tab)

Cosmonauts

Meet the people behind the possibility. Get inspired by the people who build, teach, and share, then find your own path from learner to community leader.

From learner to community leader

Plot your path toward Cosmonaut recognition and Microsoft MVP.

Start by making a meaningful contribution. Grow expertise, help others, and build a body of work you're proud to share.

Understand the Microsoft MVP award (opens in new tab)
  1. Build real expertise. Create with Azure Cosmos DB. DP-420 can validate your skills; it is not a stated requirement for either recognition.
  2. Contribute consistently. Share useful projects, explain what you learned, answer questions, speak, and mentor.
  3. Connect with the Azure Cosmos DB community. Participate and share your work. Cosmonauts are nominated, so visible, consistent contributions are how you get noticed.
  4. Explore Microsoft MVP nomination. Document impactful, verifiable contributions from the last 12 months. A current MVP or Microsoft employee must nominate you before the application and review.

Cosmonaut recognition and Microsoft MVP are separate. Passing DP-420 or participating does not guarantee either. Cosmonauts are nominated; there is no public Cosmonaut application process.

Events & updates

Get together with the community and the product team, and keep up with what's new.

Updates

The latest Azure Cosmos DB announcements from Azure Updates.

  • Generally Available

    Azure Cosmos DB Safe Key Rotation

    Safe Key Rotation for Azure Cosmos DB is now generally available. You can view timestamp metadata showing when each account key was last used, helping you identify…

    Read the update (opens in new tab)
  • Retirement

    Azure Synapse Link for Azure Cosmos DB NoSQL

    As of March 31, 2026, new Azure Cosmos DB NoSQL accounts can no longer enable Azure Synapse Link.

    Read the update (opens in new tab)
  • Public Preview

    Azure Backup for Cosmos DB

    You can now enable vaulted backups for Azure Cosmos DB accounts, protecting mission-critical data with secure, isolated, and resilient backups.

    Read the update (opens in new tab)
  • Generally Available

    Azure Cosmos DB Linux emulator (vNext)

    We are announcing the general availability of the Azure Cosmos DB Linux emulator (vNext), a cross-platform, Docker-based emulator for local development and testing against Azure Cosmos DB for NoSQL.

    Read the update (opens in new tab)
  • Public Preview

    OmniVec, an open-source embedding toolkit for Azure

    You can now automate embedding generation from multiple data sources into Azure Cosmos DB and other Azure destinations.

    Read the update (opens in new tab)
  • Public Preview

    Integrated embeddings for Azure Cosmos DB for NoSQL

    Building AI applications on Azure Cosmos DB just got simpler. With integrated embeddings, now in public preview, Azure Cosmos DB for NoSQL can automatically generate and…

    Read the update (opens in new tab)
  • Public Preview

    Safe key rotation for Azure Cosmos DB

    The safe key rotation feature helps you confidently rotate your Azure Cosmos DB account keys by providing visibility into when each key was last used.

    Read the update (opens in new tab)
  • Public Preview

    Agent Memory Toolkit for Azure Cosmos DB

    You can now accelerate the development of agentic applications with the new Agent Memory Toolkit for Azure Cosmos DB.

    Read the update (opens in new tab)
  • Public Preview

    Semantic reranker in Azure Cosmos DB

    You can now improve the relevance of any Cosmos DB query or search with the public preview of semantic reranker in Azure Cosmos DB.

    Read the update (opens in new tab)
  • Public Preview

    Agentic Retrieval Toolkit for Azure Cosmos DB

    We are announcing the public preview of the Agentic Retrieval Toolkit for Azure Cosmos DB.

    Read the update (opens in new tab)
  • Generally Available

    Azure Cosmos DB global secondary indexes

    Global secondary indexes (GSIs) for Azure Cosmos DB are now generally available, giving you a powerful way to accelerate query performance without adding complexity to your application code.

    Read the update (opens in new tab)

See all Azure Cosmos DB updates (opens in new tab)