From 9ed7ae37b6e35dcdc5749c615f2957865ea535bc Mon Sep 17 00:00:00 2001
From: prrao87 <35005448+prrao87@users.noreply.github.com>
Date: Fri, 20 Feb 2026 11:02:30 -0500
Subject: [PATCH 1/3] Add docs that explain namespaces
---
docs/api-reference/index.mdx | 4 +-
docs/docs.json | 5 +-
docs/features.mdx | 99 ------------------
docs/lance.mdx | 5 +
docs/namespaces.mdx | 74 +++++++++++++
docs/snippets/connection.mdx | 8 ++
.../images/namespaces/lance-namespace.png | Bin 0 -> 276072 bytes
docs/tables/namespaces.mdx | 74 +++++++++++++
tests/py/test_connection.py | 42 ++++++++
tests/rs/connection.rs | 32 ++++++
tests/ts/connection.test.ts | 24 ++++-
11 files changed, 264 insertions(+), 103 deletions(-)
delete mode 100644 docs/features.mdx
create mode 100644 docs/namespaces.mdx
create mode 100644 docs/static/assets/images/namespaces/lance-namespace.png
create mode 100644 docs/tables/namespaces.mdx
diff --git a/docs/api-reference/index.mdx b/docs/api-reference/index.mdx
index d3e5168..2607aa9 100644
--- a/docs/api-reference/index.mdx
+++ b/docs/api-reference/index.mdx
@@ -10,6 +10,9 @@ refer to the API documentation linked below.
If you're looking for a REST API reference, visit the [REST API](/api-reference/rest) page.
+If you're looking for conceptual and practical namespace guidance before diving into method signatures, see
+[Namespaces and Catalog Model](/namespaces) and [Using Namespaces in SDKs](/tables/namespaces).
+
## Supported SDKs
Python, Typescript and Rust SDKs are officially supported by LanceDB.
@@ -29,4 +32,3 @@ Other language SDKs are available through examples or third-party contributions.
| [Java API Quickstart]https://lancedb.github.io/lancedb/java/java/)| Streamline REST API interactions in Java|
{/* TODO: Add Go bindings reference page here */}
-
diff --git a/docs/docs.json b/docs/docs.json
index a30abbd..e495e22 100644
--- a/docs/docs.json
+++ b/docs/docs.json
@@ -40,7 +40,7 @@
"pages": [
"index",
"lance",
- "features"
+ "namespaces"
]
},
{
@@ -80,6 +80,7 @@
"tables/multimodal",
"tables/schema",
"tables/update",
+ "tables/namespaces",
"tables/versioning",
"tables/consistency"
]
@@ -383,4 +384,4 @@
"destination": "tutorials/search/:slug*"
}
]
-}
\ No newline at end of file
+}
diff --git a/docs/features.mdx b/docs/features.mdx
deleted file mode 100644
index 6c5c1b9..0000000
--- a/docs/features.mdx
+++ /dev/null
@@ -1,99 +0,0 @@
----
-title: "Feature catalog"
-sidebarTitle: "Feature catalog"
-description: "An outline of all the features offered by LanceDB, across its open source, cloud, and enterprise offerings."
-icon: "grip-vertical"
-mode: "wide"
----
-
-## Storage
-
-LanceDB provides flexible storage backends that support both cloud object storage and local high-performance storage for different deployment scenarios.
-
-| Feature | Description | OSS | Cloud | Enterprise |
-|:---|:---|:---:|:---:|:---:|
-| [Object, File, Block Storage](/storage/) | Support for AWS, GCS, Azure and S3-compatible vendors. | ✅ | ✅ | ✅ |
-| [Local SSD/NVMe Storage](/storage/) | Support for storage on customer's custom servers. | ✅ | | ✅ |
-
-## Tables
-
-LanceDB's table abstraction provides ACID-compliant data management with schema evolution, versioning, and consistency guarantees for vector and scalar data.
-
-| Feature | Description | OSS | Cloud | Enterprise |
-|:---|:---|:---:|:---:|:---:|
-| [Tables - CRUD Operations](/tables/) | Basic API to create, read, update, drop tables. | ✅ | ✅ | ✅ |
-| [Tables - Data Evolution](/tables/schema/) | Alter column schema, datatype, backfill + merge data | ✅ | ✅ | ✅ |
-| [Tables - Versioning](/tables/versioning/) | Append, overwrite, check versions + tag them. | ✅ | ✅ | ✅ |
-| [Tables - Consistency](/tables/consistency/) | Synchronize database with underlying storage. | ✅ | ✅ | ✅ |
-
-## Ingestion
-
-LanceDB's ingestion pipeline handles both vector embedding generation and data loading with support for multiple formats and efficient batch operations.
-
-| Feature | Description | OSS | Cloud | Enterprise |
-|:---|:---|:---:|:---:|:---:|
-| [Embedding - Text Data](/embedding/) | Generate vector embeddings from text data using various embedding models. | ✅ | ✅ | ✅ |
-| [Embedding - Multimodal Data](/embedding/) | Generate embeddings from images, audio, and other multimodal content. | ✅ | ✅ | ✅ |
-| [Embedding - CPU & GPU Device Configuration](/embedding/) | Configure CPU or GPU acceleration for embedding generation performance. | ✅ | ✅ | ✅ |
-| [Embedding - Environment Variables](/embedding/) | Manage API keys and configuration for embedding model access. | ✅ | ✅ | ✅ |
-| [Data Ingestion - Default](/tables/create/) | Formerly called Adding Data to a Table. | ✅ | ✅ | ✅ |
-| [Data Ingestion - Formats](/tables/create/) | Pandas, Polars, Pyarrow, Pydantic | ✅ | ✅ | ✅ |
-| [Data Ingestion - Upsert](/tables/update/) | Update existing records or insert new ones based on key. | ✅ | ✅ | ✅ |
-| [Data Ingestion - Merge Insert](/tables/update/) | Combine data from multiple sources into a single table. | ✅ | ✅ | ✅ |
-
-## Indexing
-
-LanceDB's indexing system provides multiple vector and scalar index types with automated optimization for fast similarity search and retrieval operations.
-
-| Feature | Description | OSS | Cloud | Enterprise |
-|:---|:---|:---:|:---:|:---:|
-| [Vector Index - IVF_FLAT](/indexing/vector-index/) | Minimal index that looks at IVF partitions, instead of brute forcing. | ✅ | ✅ | ✅ |
-| [Vector Index - IVF_PQ](/indexing/vector-index/) | Default vector index using Euclidean distance. | ✅ | ✅ | ✅ |
-| [Vector Index - IVF_SQ](/indexing/vector-index/) | IVF index built using scalar quantized vectors. | ✅ | ✅ | ✅ |
-| [Vector Index - IVF_HNSW_SQ](/indexing/vector-index/) | HNSW built on IVF's partitions + vectors that are scalar quantized. | ✅ | ✅ | ✅ |
-| [Vector Index - Binary](/indexing/vector-index/) | IVF_FLAT with Hamming distance for binary vectors. | ✅ | ✅ | ✅ |
-| [Scalar Index](/indexing/scalar-index/) | BTREE, BITMAP, LABEL_LIST | ✅ | ✅ | ✅ |
-| [Automated Indexing](/indexing/vector-index/) | Indexing happens in the background no config. | | ✅ | ✅ |
-| [Bypass Automated Indexing](/indexing/) | When you want to search over all available vectors. | ✅ | ✅ | ✅ |
-| [Reindexing - Manual](/indexing/reindexing/) | User needs to specify that they want to reindex. | ✅ | ✅ | ✅ |
-| [Reindexing - Automated](/indexing/reindexing/) | Reindexing happens in the background no config | | ✅ | ✅ |
-| [GPU Indexing - Manual](/indexing/gpu-indexing/) | User needs to specify which indexing device to use. | ✅ | ✅ | ✅ |
-| [GPU Indexing - Automated](/indexing/gpu-indexing/) | Indexing device is automatically set for user. | | ✅ | ✅ |
-| [Full Text Search Index](/indexing/fts-index/) | Inverted index | ✅ | ✅ | ✅ |
-
-## Search
-
-LanceDB's search capabilities combine vector similarity search, full-text search, and hybrid approaches to provide comprehensive retrieval functionality across different data types.
-
-| Feature | Description | OSS | Cloud | Enterprise |
-|:---|:---|:---:|:---:|:---:|
-| [Vector Search - No Index](/search/vector-search/) | Goes through all the available vectors. | ✅ | ✅ | ✅ |
-| [Vector Search - ANN Index](/search/vector-search/) | Retrieves top K similar vectors. | ✅ | ✅ | ✅ |
-| [Vector Search - Multivectors](/search/multivector-search/) | Late interaction vector search. | ✅ | ✅ | ✅ |
-| [Vector Search - Distance Range](/search/vector-search/) | Search for vectors within a specific distance threshold. | ✅ | ✅ | ✅ |
-| [Vector Search - Binary Vectors](/search/vector-search/) | Search using binary vector representations for efficiency. | ✅ | ✅ | ✅ |
-| [Vector Search - Filtering](/search/filtering/) | Apply scalar filters during vector search operations. | ✅ | ✅ | ✅ |
-| [Vector Search - Batch API](/search/vector-search/) | Process multiple search queries in a single request. | ✅ | ✅ | ✅ |
-| [Vector Search - Async Indexing](/search/vector-search/) | Fallback brute force for fast performance. | | ✅ | ✅ |
-| [Full Text Search - FTS Index](/search/full-text-search/) | Inverted Index | ✅ | ✅ | ✅ |
-| [Full Text Search - Tokenizer](/search/full-text-search/) | Ngram and other common methods of splitting text data. | ✅ | ✅ | ✅ |
-| [Full Text Search - Scalar Index](/search/full-text-search/) | BTREE, BITMAP, LABEL_LIST for non-vector data. | ✅ | ✅ | ✅ |
-| [Full Text Search - Fuzzy Search](/search/full-text-search/) | Searching when there is a typo on the query. | ✅ | ✅ | ✅ |
-| [Full Text Search - Prefix Matching](/search/full-text-search/) | Search for text that starts with specific characters. | ✅ | ✅ | ✅ |
-| [Full Text Search - Score Boosting](/search/full-text-search/) | Increase relevance scores for specific terms or fields. | ✅ | ✅ | ✅ |
-| [Full Text Search - Boolean Logic](/search/full-text-search/) | Use AND, OR, NOT operators in text search queries. | ✅ | ✅ | ✅ |
-| [Full Text Search - Array Fields](/search/full-text-search/) | Search within array or list data types. | ✅ | ✅ | ✅ |
-| [Hybrid Search - FTS Index](/search/hybrid-search/) | Combine vector and full-text search in single query. | ✅ | ✅ | ✅ |
-| [Hybrid Search - Reranking](/search/hybrid-search/) | Reorder search results using additional ranking models. | ✅ | ✅ | ✅ |
-| [SQL Queries](/search/sql) | Execute standard SQL queries on LanceDB tables. | ✅ | ✅ | ✅ |
-| [Query Optimization](/search/optimize-queries/) | Explain query plan, analyze query plan, optimization config settings. | ✅ | ✅ | ✅ |
-
-## Filtering
-
-LanceDB's filtering system provides flexible query capabilities that can be applied independently or in combination with vector and full-text search operations.
-
-| Feature | Description | OSS | Cloud | Enterprise |
-|:---|:---|:---:|:---:|:---:|
-| [Filtering - no Vector Search](/search/filtering/) | Apply filters without vector search operations. | ✅ | ✅ | ✅ |
-| [Filtering - Vector Search](/search/filtering/) | Apply filters during vector search operations. | ✅ | ✅ | ✅ |
-| [Filtering - Full Text Search](/search/filtering/) | Apply filters during full-text search operations. | ✅ | ✅ | ✅ |
\ No newline at end of file
diff --git a/docs/lance.mdx b/docs/lance.mdx
index 0f5faa0..073341e 100644
--- a/docs/lance.mdx
+++ b/docs/lance.mdx
@@ -24,6 +24,11 @@ complete open lakehouse on top of object storage to power AI workflows. The form
high-performance vector search, full-text search, random access, and feature engineering capabilities
to a single unified system, eliminating the need for multiple specialized databases.
+
+LanceDB operates at the catalog layer. To understand how namespaces fit into the Lance file/table/catalog stack,
+see [Namespaces and Catalog Model](/namespaces-catalog-model), then [Using Namespaces in SDKs](/tables/namespaces).
+
+
Unlike traditional vector databases that only store embeddings alongside the metadata, LanceDB's
multimodal lakehouse stores both the original data (including image, video or audio bytes)
and its vector representations alongside traditional tabular data in the same efficient format.
diff --git a/docs/namespaces.mdx b/docs/namespaces.mdx
new file mode 100644
index 0000000..03ab60d
--- /dev/null
+++ b/docs/namespaces.mdx
@@ -0,0 +1,74 @@
+---
+title: "Namespaces and the Catalog Model"
+sidebarTitle: "Namespaces"
+description: "Understand LanceDB as a catalog-level abstraction over Lance's table format, and learn how namespaces help organize Lance tables."
+icon: "sitemap"
+keywords: ["namespace", "catalog", "lance format", "table format", "lancedb"]
+---
+
+Despite its name, LanceDB is not a "database" in the traditional sense -- it is a **Multimodal Lakehouse** that builds on the table abstraction,
+similar to many other lakehouse projects. LanceDB exposes a catalog-level abstraction over the Lance table format, via a *namespace spec*.
+
+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 a `namespace` parameter as input.
+
+## 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.
+
+
+
+## Root namespace and the familiar `data/` layout
+
+The simplest namespace model in LanceDB is a single root namespace, often represented by one
+directory:
+
+```bash
+/data/ # root namespace
+├─ users.lance # table ["users"] in root
+└─ orders.lance # table ["orders"] in root
+```
+
+As a user of LanceDB, you might never notice namespaces at first, because LanceDB exposes the single-level
+hierarchy shown above, with hte data being stored in the `data/` directory`, wher the root namespace
+is implicit. In alternative setups, you could have multiple namespaces that we won't covere here,
+but you can more about them in the [namespace documentation](https://lance.org/format/namespace/) for the Lance format.
+
+## Best-practice guidance
+
+- Use the default, single-level root namespace in LanceDB for locally stored, single applications or early-stage projects.
+- 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"`).
+- Avoid hard-coding object-store table paths in application code -- instead, prefer catalog identifiers + namespaces.
+
+See the Python example below for how to use namespaces in practice.
+
+```python Python icon="python"
+import lancedb
+
+# App config: only the catalog endpoint/root is configured once.
+db = lancedb.connect("s3://my-lakehouse/catalog")
+
+# Business identifier + namespace path (stable app-level IDs)
+namespace = ["prod", "recommendations"]
+table_name = "user_profiles"
+
+# Good: resolve table through catalog + namespace
+table = db.open_table(table_name, namespace=namespace)
+
+# Bad: Avoid hard-coded physical object-store table paths
+# (it's bad for maintainability reasons)
+# table = lancedb.connect(
+# "s3://my-lakehouse/catalog/prod/recommendations/user_profiles.lance"
+# )
+```
+
+## SDK usage
+
+1. For language-specific examples of `namespace` usage across Python, TypeScript, and Rust, see "[Using namespaces in SDKs](/tables/namespaces)".
+2. For REST-level operations, see the [REST API Reference](/api-reference/rest).
diff --git a/docs/snippets/connection.mdx b/docs/snippets/connection.mdx
index 5977a33..2e08f2d 100644
--- a/docs/snippets/connection.mdx
+++ b/docs/snippets/connection.mdx
@@ -6,15 +6,23 @@ export const PyConnectCloud = "uri = \"db://your-database-uri\"\napi_key = \"you
export const PyConnectObjectStorage = "import lancedb\n\nuri = \"s3://your-bucket/path\"\n# You can also use \"gs://your-bucket/path\" or \"az://your-container/path\".\ndb = lancedb.connect(uri)\n";
+export const PyNamespaceAdminOps = "import lancedb\n\ndb = lancedb.connect(\"./data/sample-lancedb\")\ndb.create_namespace([\"prod\"])\ndb.create_namespace([\"prod\", \"search\"])\n\nchild_namespaces = db.list_namespaces(namespace=[\"prod\"]).namespaces\nmetadata = db.describe_namespace([\"prod\", \"search\"])\n\ndb.drop_namespace([\"prod\", \"search\"], mode=\"skip\")\ndb.drop_namespace([\"prod\"], mode=\"skip\")\n";
+
+export const PyNamespaceTableOps = "import lancedb\n\ndb = lancedb.connect(\"./data/sample-lancedb\")\nnamespace = [\"prod\", \"search\"]\n\ndb.create_table(\n \"users\",\n data=[{\"id\": 1, \"name\": \"alice\"}],\n mode=\"overwrite\",\n namespace=namespace,\n)\n\ntable = db.open_table(\"users\", namespace=namespace)\ntables = db.list_tables(namespace=namespace).tables\n\ndb.drop_table(\"users\", namespace=namespace)\n# drop_all_tables is namespace-aware as well:\n# db.drop_all_tables(namespace=namespace)\n";
+
export const TsConnect = "import * as lancedb from \"@lancedb/lancedb\";\n\nasync function connectExample(uri: string) {\n const db = await lancedb.connect(uri);\n return db;\n}\n";
export const TsConnectCloud = "const uri = \"db://your-database-uri\";\nconst apiKey = \"your-api-key\";\nconst region = \"us-east-1\";\n";
export const TsConnectObjectStorage = "async function connectObjectStorageExample() {\n const uri = \"s3://your-bucket/path\";\n // You can also use \"gs://your-bucket/path\" or \"az://your-container/path\".\n const db = await lancedb.connect(uri);\n return db;\n}\n";
+export const TsNamespaceTableOps = "const db = await lancedb.connect(uri);\nconst namespace = [\"prod\", \"search\"];\n\nawait db.createTable(\n \"users\",\n [{ id: 1, name: \"alice\" }],\n namespace,\n { mode: \"overwrite\" },\n);\n\nconst table = await db.openTable(\"users\", namespace);\nconst tableNames = await db.tableNames(namespace);\n\nawait db.dropTable(\"users\", namespace);\n// dropAllTables is namespace-aware as well:\n// await db.dropAllTables(namespace);\n";
+
export const RsConnect = "async fn connect_example(uri: &str) {\n let db = connect(uri).execute().await.unwrap();\n let _ = db;\n}\n";
export const RsConnectCloud = "let uri = \"db://your-database-uri\";\nlet api_key = \"your-api-key\";\nlet region = \"us-east-1\";\n";
export const RsConnectObjectStorage = "let uri = \"s3://your-bucket/path\";\n// You can also use \"gs://your-bucket/path\" or \"az://your-container/path\".\n";
+export const RsNamespaceTableOps = "let conn = connect(uri).execute().await?;\nlet namespace = vec![\"prod\".to_string(), \"search\".to_string()];\n\nlet schema = std::sync::Arc::new(arrow_schema::Schema::new(vec![\n arrow_schema::Field::new(\"id\", arrow_schema::DataType::Int64, false),\n]));\n\nconn.create_empty_table(\"users\", schema)\n .namespace(namespace.clone())\n .execute()\n .await?;\n\nlet _table = conn\n .open_table(\"users\")\n .namespace(namespace.clone())\n .execute()\n .await?;\nlet _table_names = conn\n .table_names()\n .namespace(namespace.clone())\n .execute()\n .await?;\n\nconn.drop_table(\"users\", &namespace).await?;\n// drop_all_tables is namespace-aware as well:\n// conn.drop_all_tables(&namespace).await?;\n";
+
diff --git a/docs/static/assets/images/namespaces/lance-namespace.png b/docs/static/assets/images/namespaces/lance-namespace.png
new file mode 100644
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