Tables and Namespaces

Learn more about the table abstraction and namespaces in LanceDB.

Despite its name, LanceDB is not a “database” in the traditional sense. It is a Multimodal Lakehouse built on Lance tables plus a catalog abstraction. As you dive deeper into LanceDB, it helps to separate two ideas:

• A table is where your data lives and is queried.
• A namespace is how groups of tables are organized and resolved at the catalog level.

Understanding tables

A table is the core data abstraction in LanceDB: a structured dataset with schema, indexes, and versioned updates. What changes between deployments is how that table is addressed and accessed.

The mental model below clarifies table types by connection mode:

• LanceTable: direct table access (local path, file://, s3://, and similar object-store paths). This is the common mode in LanceDB OSS.
• RemoteTable: catalog-backed table access through a server/cluster (db://...). This is the mode you will use in LanceDB Enterprise.

From an application perspective, both expose a familiar table API: create/open tables, mutate rows, and query data. The main difference is where resolution and execution happen (directly against storage vs through a remote catalog service).

Semantic difference between tables and namespaces

The easiest way to think about this is:

• A table answers: “What data do I store and query?”
• A namespace answers: “Where does this table name live in my catalog hierarchy?”

In other words, tables are data objects; namespaces are catalog objects.

Concept	Scope	Owns	Typical operations
Table	Data layer	Schema, rows, indexes, versions	create_table, open_table, inserts/updates/deletes, search/query
Namespace	Catalog layer	Hierarchy of names, table grouping, table name resolution	create_namespace, list_namespaces, drop_namespace, table ops with namespace

For simple use cases where you have a relatively flat set of tables, you can ignore namespaces and just use table paths directly. As your application needs evolve and your tables grow in number and complexity, you may move from table-centric thinking to catalog-centric thinking. Check out the Namespaces and the Catalog Model guide to learn more.