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This quickstart follows a similar workflow as the OSS quickstart, but uses a RemoteTable through a db://... connection.
To get a LanceDB Enterprise cluster setup and to obtain credentials and endpoint details, contact our team to get started. This guide assumes your Enterprise cluster is already running.

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1. Install LanceDB

pip install lancedb

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2. Connect to Enterprise (db://...)

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3. Create a table (same sample data as the OSS quickstart)

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5. Open table, add data, and query again

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Differences between Enterprise and OSS usage

As can be seen, the flow for working with a RemoteTable in Enterprise looks more or less similar to the OSS quickstart. However, there are some semantic differences:

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1. Connection model

In LanceDB Enterprise, your app connects via a db://... URI and sends requests to the cluster API. The cluster executes table operations on your behalf. Your code is coupled to a managed service endpoint (whereas in OSS, your code is directly coupled to storage paths).

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2. Returned table type

Connecting to an Enterprise table via open_table(...) returns a RemoteTable, unlike in OSS, which returns a LanceTable.

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3. Materialization APIs

For Python users working with LanceDB Enterprise, RemoteTable does not support table-level materialization methods like table.to_arrow() or table.to_pandas(). This is to protect users from accidentally materializing tables that are too large to fit in memory. Instead, you materialize results through query/search builders, for example table.search(...).limit(...).to_pandas() or table.query(...).to_arrow(). For quick previews, you can use table.head().

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4. Maintenance lifecycle

In Enterprise, maintenance operations like optimize, compact_files are handled by the cluster as background work. You can trigger them manually, but they are not required for performance or correctness in the same way they are in OSS. That means maintenance is managed by platform behavior and cluster configuration, not by explicit per-table maintenance calls in your application code.

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5. Guardrails and limits

Enterprise can enforce platform-level guardrails, such as index/table limits and safety checks around operations like merge_insert when too many rows are unindexed. OSS mostly exposes storage/format-level behavior, and you tune many lifecycle tasks yourself. This means an operation in LanceDB Enterprise can fail due to service-level policy, not just because of local table shape or schema mismatch.

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6. Cluster-managed background work

In Enterprise, async writes and reindexing workflows are handled by cluster background systems. In OSS, if you want ongoing upkeep, you usually schedule and run it yourself in your application or jobs. In practice, your app issues table operations, and the platform handles distributed orchestration for maintenance and indexing in the background.
As a rule of thumb, all you need to remember with regard to LanceDB Enterprise is this: treat db://... as a remote service boundary, use query builders to fetch results, and otherwise interact with your tables as you would in OSS.**

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Advanced usage via namespace-backed connections

LanceDB Enterprise also supports namespace-backed catalog connections. This allows you to resolve tables by namespace, rather than by direct URI, and is accessed via the REST connection mode of connect_namespace(...). This is useful when table location resolution and credential vending are handled by an external catalog/namespace service.
Python
import os
import lancedb

ns_db = lancedb.connect_namespace(
    "rest",
    {
        "uri": "https://<your-catalog-endpoint>",
        "headers.Authorization": f"Bearer {os.environ['CATALOG_TOKEN']}",
    },
)

# Namespace-scoped table resolution
table = ns_db.open_table("adventurers", namespace=["prod", "search"])
This mode is useful when table location resolution and credential vending are handled by an external catalog/namespace service. If you want to stick to a common table flow, start with the db:// RemoteTable flow shown above.

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Further reading

You can learn more about table operations, namespaces, and the architecture of LanceDB Enterprise in the following guides.

Table operations

Build on this quickstart with table creation, updates, and schema tips.

Using namespaces

Learn how to use namespaces in LanceDB, and connect to an Enterprise namespace via REST.

LanceDB Enterprise architecture

Learn about the architecture of LanceDB Enterprise and how it achieves high performance at scale.