> ## Documentation Index > Fetch the complete documentation index at: https://docs.lancedb.com/llms.txt > Use this file to discover all available pages before exploring further. # Namespaces > Grouping tables into a hierarchy, and addressing them through it. **Applies to:** Embedded ✅, Enterprise ✅ LanceDB organizes Lance tables through a catalog-level abstraction defined by the *namespace spec*. LanceDB Embedded is an embedded library for accessing those tables, and LanceDB Enterprise is a multimodal lakehouse that provides shared compute and catalog services on top of the Lance format. If you're coming from traditional databases or lakehouses, you can think of a namespace as the catalog path that says where a table name lives. Lance provides the **file** and **table** formats to store and manage your data and indexes. LanceDB operates at the catalog layer (used to organize, discover, and operate on many Lance tables) and provides a compute engine on top of the Lance format. This is why many SDK methods in LanceDB, like `create_table`, `open_table`, `drop_table`, and `rename_table`, accept namespace input. The SDK methods expose that input in the idiom of each language: Python uses `namespace_path`, Rust uses builder methods like `.namespace(...)`, and TypeScript uses `namespacePath` arguments. > [!NOTE] > > In LanceDB Enterprise SQL, a namespaced table is addressed by its > [schema](https://docs.lancedb.com/basics/catalog.md#schema) -- the namespace path joined by `$`, not > by `.` -- [before the table name](https://docs.lancedb.com/sql/dql/select.md#namespaces). ## Namespace hierarchy Namespaces are generalizations of catalog specs that give platform developers a clean way to present Lance tables in the structures users expect. The diagram below shows how the hierarchy can go beyond a single level. A namespace can contain a collection of tables, and it can also contain namespaces recursively. ![](https://mintcdn.com/lancedb-bcbb4faf/I3MiwGknMI2Eqk_L/static/assets/images/namespaces/lance-namespace.png?fit=max\&auto=format\&n=I3MiwGknMI2Eqk_L\&q=85\&s=0d1e743be6def54e5879c43d5da59c33) Before diving into examples, it helps to keep two terms in mind: the **namespace client** is the abstraction that presents a consistent namespace API, while the **namespace implementation** is the concrete backend that resolves namespaces and table locations (for example, a local directory or an external catalog). If you want to go deeper, see the Lance format [namespace documentation](https://lance.org/format/namespace/). ## Namespace paths and names A namespace path is a list of components. For example, `["prod", "search"]` means the `search` namespace inside the `prod` namespace. The empty path, `[]`, means the root namespace. Each component is a name, not a filesystem path segment, and can't be empty. Keep each one to letters, numbers, underscores, hyphens, and periods, so the same identifier is usable everywhere: a local directory namespace accepts other characters too, but other namespace implementations and deployments can refuse them. [Naming rules](https://docs.lancedb.com/basics/naming.md) has the lengths and the other limits. ## Directory namespaces The simplest namespace model in LanceDB is a single root namespace, often represented by one directory. Namespaces can nest inside it, as in this hierarchy: ```bash theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} ./local_lancedb (root) └── prod └── search └── user (table) └── data (table) ``` The hierarchy is logical, not a tree of folders: a directory namespace records it in a `__manifest` table in the root directory, and stores each table in a directory of its own there. As a user of LanceDB Embedded, you might never notice namespaces at first, because a plain connection uses only the root namespace, which is implicit. Connecting to this namespace is as simple as connecting to the namespace root: ```python Python icon="python" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} # Connect to the directory namespace root db = lancedb.connect("./local_lancedb") ``` ```typescript TypeScript icon="square-js" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} import * as lancedb from "@lancedb/lancedb"; // Connect to the directory namespace root const db = await lancedb.connect("./local_lancedb"); ``` ```rust Rust icon="rust" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} use lancedb::connect; // Connect to the directory namespace root let db = connect("./local_lancedb").execute().await?; ``` A table created through this connection is stored directly under that path, as `.lance`. You can also explicitly connect to a namespace using `lancedb.connect_namespace(...)` with the directory namespace implementation: ```python Python icon="python" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} # Local DirectoryNamespace root # See https://lance.org/format/namespace/dir/catalog-spec/ db = lancedb.connect_namespace("dir", {"root": "./local_lancedb"}) table_name = "user" data = [{"id": 1, "vector": [0.1, 0.2], "name": "alice"}] table = db.create_table(table_name, data=data, mode="create") print(f"Created table: {table.name}") # Created table: user ``` ```typescript TypeScript icon="square-js" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} import * as lancedb from "@lancedb/lancedb"; // Local DirectoryNamespace root // See https://lance.org/format/namespace/dir/catalog-spec/ const db = await lancedb.connectNamespace("dir", { root: "./local_lancedb" }); const table = await db.createTable( "user", [{ id: 1, vector: [0.1, 0.2], name: "alice" }], { mode: "create" }, ); console.log(`Created table: ${table.name}`); // Created table: user ``` ```rust Rust icon="rust" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} use std::collections::HashMap; use std::sync::Arc; use arrow_schema::{DataType, Field, Schema}; // Local DirectoryNamespace root // See https://lance.org/format/namespace/dir/catalog-spec/ let mut properties = HashMap::new(); properties.insert("root".to_string(), "./local_lancedb".to_string()); let db = lancedb::connect_namespace("dir", properties) .execute() .await?; let schema = Arc::new(Schema::new(vec![ Field::new("id", DataType::Int64, false), ])); let table = db .create_empty_table("user", schema) .execute() .await?; println!("Created table: {}", table.name()); // Created table: user ``` > [!NOTE] > > * For simple use cases in LanceDB Embedded, you don't need to go too deep into namespaces. > * To integrate LanceDB with external catalogs, understand how each namespace implementation resolves table names and locations in your organization's setup. ## Remote or external catalog namespaces The example above showed local directory-based namespaces. LanceDB also supports namespaces backed by remote object stores and external catalogs, via the REST namespace implementation. For remote object stores with central metadata or catalog services (either commercial or open source), use the REST namespace implementation. It is backed by REST routes (for example `POST /v1/namespace/{id}/create` and `GET /v1/namespace/{id}/list`) and server-provided table locations. For authentication, any property prefixed with `headers` is forwarded as an HTTP header (for example `headers.Authorization` becomes `Authorization`, and `headers.X-API-Key` becomes `X-API-Key`). LanceDB Enterprise REST requests use the `x-api-key` header for API-key authentication. Deployments that route multiple databases through the same endpoint can also use headers such as `x-lancedb-database` or `x-lancedb-database-prefix` for database context. Replace the catalog URL and credential placeholders below with your values. In application code, load credentials from environment variables or a secrets manager. ```python Python icon="python" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} # Remote RestNamespace root # See https://lance.org/format/namespace/rest/catalog-spec/ db = lancedb.connect_namespace( "rest", { "uri": "https://.internal..com", "headers.x-api-key": "your-api-key", # or: # "headers.Authorization": "Bearer your-access-token", }, ) ``` ```typescript TypeScript icon="square-js" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} import * as lancedb from "@lancedb/lancedb"; // Remote RestNamespace root // See https://lance.org/format/namespace/rest/catalog-spec/ const db = await lancedb.connectNamespace("rest", { uri: "https://.internal..com", headers: { "x-api-key": "your-api-key", // or: // Authorization: "Bearer your-access-token", }, }); ``` ```rust Rust icon="rust" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} use std::collections::HashMap; // Remote RestNamespace root // See https://lance.org/format/namespace/rest/catalog-spec/ let mut properties = HashMap::new(); properties.insert( "uri".to_string(), "https://.internal..com".to_string(), ); properties.insert( "headers.x-api-key".to_string(), "your-api-key".to_string(), ); // or: // properties.insert( // "headers.Authorization".to_string(), // "Bearer your-access-token".to_string(), // ); let db = lancedb::connect_namespace("rest", properties) .execute() .await?; ``` [LanceDB Enterprise](https://docs.lancedb.com/index.md#architecture) operates a REST namespace server on top of the Lance format, so any REST client that can speak the REST namespace API contract can be used to interact with it. It does not serve the contract's `exists` routes, so existence checks made through a direct REST namespace client fail against it. Python remote connections created with `lancedb.connect("db://...")` or `lancedb.connect_async("db://...")` support `namespace_exists` and `table_exists` through the existing describe routes instead. For authentication examples in LanceDB Enterprise, visit the [Namespaces in SDKs](#namespaces-in-lancedb-enterprise) page. ## Best practices Below, we list some best practices for working with namespaces: * For simple use cases and single, stand-alone applications, the directory-based root namespace is sufficient and requires no special configuration. * For remote storage locations, introduce explicit namespaces when multiple teams, environments, or domains share the same catalog. * Treat namespace paths as stable identifiers (for example `"prod/search"`, `"staging/recs"`). * For maintainability reasons, avoid hard-coding object-store table paths in application code. Instead, prefer catalog identifiers + namespaces. ## Table operations with namespace paths Let's imagine a scenario where your table management needs have evolved, and you now have the following multi-level structure to organize your tables outside the root namespace. ``` ./local_lancedb (root) └── prod └── search └── user (table) └── data (table) └── recommendations └── user (table) └── data (data) ``` Below, we show how you would express table operations within that namespace. Each item in the namespace list (`["prod", "search"]`) represents a level in the namespace hierarchy, and the table name is specified when you create, open, list, or drop it. The SDK methods expose the namespace path in the idiom of each language: * Python: pass `namespace_path=["prod", "search"]` to table operations. * Rust: call builder methods such as `.namespace(vec!["prod".to_string(), "search".to_string()])`. * TypeScript: pass a `namespacePath` array, for example `await db.openTable("user", ["prod", "search"])`. ```python Python icon="python" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} import lancedb db = lancedb.connect_namespace("dir", {"root": "./local_lancedb"}) # Create namespace tree: prod/search db.create_namespace(["prod"], mode="exist_ok") db.create_namespace(["prod", "search"], mode="exist_ok") db.create_namespace(["prod", "recommendations"], mode="exist_ok") db.create_table( "user", data=[{"id": 1, "vector": [0.1, 0.2], "name": "alice"}], namespace_path=["prod", "search"], mode="create", # use "overwrite" only if you want to replace existing table ) db.create_table( "user", data=[{"id": 2, "vector": [0.3, 0.4], "name": "bob"}], namespace_path=["prod", "recommendations"], mode="create", # use "overwrite" only if you want to replace existing table ) # Verify: listings return a response with the names and a page token print(db.list_namespaces().namespaces) # ['prod'] print(db.list_namespaces(namespace_path=["prod"]).namespaces) # ['recommendations', 'search'] print(db.list_tables(namespace_path=["prod", "search"]).tables) # ['user'] print(db.list_tables(namespace_path=["prod", "recommendations"]).tables) # ['user'] ``` ```typescript TypeScript icon="square-js" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} async function collectNames(items: AsyncIterable): Promise { const names: string[] = []; for await (const name of items) names.push(name); return names; } const db = await lancedb.connectNamespace("dir", { root: "./local_lancedb" }); // Create namespace tree: prod/search and prod/recommendations await db.createNamespace(["prod"], { mode: "exist_ok" }); await db.createNamespace(["prod", "search"], { mode: "exist_ok" }); await db.createNamespace(["prod", "recommendations"], { mode: "exist_ok" }); await db.createTable( "user", [{ id: 1, vector: [0.1, 0.2], name: "alice" }], ["prod", "search"], { mode: "create" }, // use "overwrite" only if you want to replace existing table ); await db.createTable( "user", [{ id: 2, vector: [0.3, 0.4], name: "bob" }], ["prod", "recommendations"], { mode: "create" }, ); // Verify console.log(await collectNames(db.listNamespaces())); // ["prod"] console.log(await collectNames(db.listNamespaces(["prod"]))); // ["recommendations", "search"] console.log(await db.tableNames(["prod", "search"])); // ["user"] console.log(await db.tableNames(["prod", "recommendations"])); // ["user"] ``` ```rust Rust icon="rust" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} let conn = connect(uri).execute().await?; let search_namespace = vec!["prod".to_string(), "search".to_string()]; let recommendations_namespace = vec!["prod".to_string(), "recommendations".to_string()]; let schema = std::sync::Arc::new(arrow_schema::Schema::new(vec![ arrow_schema::Field::new("id", arrow_schema::DataType::Int64, false), ])); conn.create_empty_table("user", schema.clone()) .namespace(search_namespace.clone()) .execute() .await?; conn.create_empty_table("user", schema) .namespace(recommendations_namespace.clone()) .execute() .await?; let search_table_names = conn .table_names() .namespace(search_namespace) .execute() .await?; let recommendation_table_names = conn .table_names() .namespace(recommendations_namespace) .execute() .await?; println!("{search_table_names:?}"); // ["user"] println!("{recommendation_table_names:?}"); // ["user"] ``` > [!NOTE] > > Using namespaces is **optional** in LanceDB, and most basic use cases do not require to work with them. > An empty namespace (`[]`), which is the default, means the root namespace, whose tables are stored > directly under the specified root path. ## Namespace management APIs You can open/create/drop tables inside a namespace path (like `["prod", "search"]`). All three SDKs expose namespace lifecycle operations directly. In Python, use `lancedb.connect_namespace(...)` when calling namespace lifecycle methods such as `create_namespace`, `list_namespaces`, `describe_namespace`, and `drop_namespace`. In TypeScript, use `lancedb.connectNamespace(...)` and call `createNamespace`, `listNamespaces`, `describeNamespace`, and `dropNamespace` on the returned `Connection`. In Rust, use `lancedb::connect_namespace(...)` and call `create_namespace`, `list_namespaces`, and `drop_namespace`. ```python Python icon="python" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} import lancedb db = lancedb.connect_namespace("dir", {"root": "./local_lancedb"}) namespace = ["prod", "search"] db.create_namespace(["prod"]) db.create_namespace(["prod", "search"]) child_namespaces = db.list_namespaces(namespace_path=["prod"]).namespaces print(f"Child namespaces under ['prod']: {child_namespaces}") # Child namespaces under ['prod']: ['search'] metadata = db.describe_namespace(["prod", "search"]) print(f"Metadata for namespace {namespace}: {metadata}") # Metadata for namespace ['prod', 'search']: properties=None db.drop_namespace(["prod", "search"], mode="skip") db.drop_namespace(["prod"], mode="skip") ``` ```typescript TypeScript icon="square-js" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} async function collectNames(items: AsyncIterable): Promise { const names: string[] = []; for await (const name of items) names.push(name); return names; } const db = await lancedb.connectNamespace("dir", { root: "./local_lancedb" }); const namespace = ["prod", "search"]; await db.createNamespace(["prod"]); await db.createNamespace(["prod", "search"]); const childNamespaces = await collectNames(db.listNamespaces(["prod"])); console.log( `Child namespaces under ${JSON.stringify(namespace)}:`, childNamespaces, ); // Child namespaces under ["prod","search"]: [ 'search' ] const metadata = await db.describeNamespace(["prod", "search"]); console.log(`Metadata for namespace ${JSON.stringify(namespace)}:`, metadata); await db.dropNamespace(["prod", "search"], { mode: "skip" }); await db.dropNamespace(["prod"], { mode: "skip" }); ``` ```rust Rust icon="rust" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} let mut properties = std::collections::HashMap::new(); properties.insert("root".to_string(), "./local_lancedb".to_string()); let db = lancedb::connect_namespace("dir", properties).execute().await?; let namespace = vec!["prod".to_string(), "search".to_string()]; db.create_namespace(lance_namespace::models::CreateNamespaceRequest { id: Some(vec!["prod".to_string()]), ..Default::default() }) .await?; db.create_namespace(lance_namespace::models::CreateNamespaceRequest { id: Some(namespace.clone()), ..Default::default() }) .await?; let child_namespaces = db .list_namespaces(lance_namespace::models::ListNamespacesRequest { id: Some(vec!["prod".to_string()]), ..Default::default() }) .await?; println!( "Child namespaces under {:?}: {:?}", namespace, child_namespaces ); // Child namespaces under ["prod", "search"]: ["search"] db.drop_namespace(lance_namespace::models::DropNamespaceRequest { id: Some(namespace.clone()), ..Default::default() }) .await?; db.drop_namespace(lance_namespace::models::DropNamespaceRequest { id: Some(vec!["prod".to_string()]), ..Default::default() }) .await?; ``` Namespace creation and deletion have modes that control what happens when the target already exists, doesn't exist, or contains data: * Create mode: `create` fails if the namespace already exists, `exist_ok` keeps the existing namespace, and `overwrite` replaces it. * Drop mode: `fail` reports an error when the namespace doesn't exist, and `skip` treats a missing namespace as a successful no-op. * Drop behavior: `restrict` keeps non-empty namespaces from being dropped, and `cascade` drops child namespaces and tables first. Namespace path components can't be empty, and are best kept to letters, numbers, underscores, hyphens, and periods, as [above](#namespace-paths-and-names). Listing APIs return the immediate children of the requested namespace path. Use `limit` with the returned `page_token` to page through large catalogs; pass an empty namespace path (`[]`) when you want to list from the root namespace. In Python, a listing returns a response: the names are in its `namespaces` or `tables`, and `page_token` is set when there is another page. ## Namespaces in LanceDB Enterprise In LanceDB Enterprise deployments, configure namespace-backed federated databases in a TOML file under your deployment's `config` directory. LanceDB Enterprise supports both directory-based (`ns_impl = "dir"`) and REST-based (`ns_impl = "rest"`) namespace implementations. The example below shows how to configure a directory-based namespace implementation in LanceDB Enterprise. ```toml theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} # Federated database configuration for DirectoryNamespace # This example uses minio storage [federated_dbs.federated_dir_test] ns_impl = "dir" root = "s3:///" "storage.region" = "us-east-1" "storage.endpoint" = "http://localhost:9000" "storage.access_key_id" = "minioadmin" "storage.secret_access_key" = "minioadmin" "storage.allow_http" = "true" # Far future expiration (year 2100) "storage.expires_at_millis" = "4102444800000" ``` The example above uses MinIO, but the same approach applies to other cloud object storage platforms based on your deployment. For REST-based namespace servers, you can specify the namespace implementation as `"rest"` with forwarding prefixed headers for authentication and context propagation. ```toml theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} [federated_dbs.federated_rest_test] ns_impl = "rest" uri = "http://.internal.catalog.com" forward_header_prefixes = ["X-forward"] ``` With `forward_header_prefixes = ["X-forward"]`, any incoming header starting with `X-forward` is forwarded to `http://.internal.catalog.com`. This is useful for auth propagation, for example sending `X-forward-authorization: Bearer xxxx`. For the LanceDB REST API itself, requests use `x-api-key` for API-key authentication. If your endpoint serves more than one database, LanceDB can also use headers such as `x-lancedb-database` or `x-lancedb-database-prefix` to route the request to the right database context. ## Privileges A namespace's `USAGE`, and the `CREATE_TABLE`, `CREATE_VIEW`, `CREATE_MATERIALIZED_VIEW`, `CREATE_NAMESPACE`, `CREATE_SECRET`, `CREATE_STORAGE_INTEGRATION` and `CREATE_FUNCTION` privileges for what it can hold, are granted through the REST ACL API or SQL `GRANT`/`REVOKE`: ```sql SQL icon="database" theme={"theme":{"light":"vitesse-light","dark":"catppuccin-mocha"}} GRANT CREATE NAMESPACE, CREATE TABLE, CREATE VIEW ON SCHEMA platform TO ROLE writers ``` See [Privileges](https://docs.lancedb.com/governance/privileges.md#sql) for the full statement syntax and every target it reaches. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.