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docs: Document Python SDK remote table to_arrow/to_pandas limitations and alternatives #128

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15 changes: 15 additions & 0 deletions docs/tables/index.mdx
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Expand Up @@ -165,6 +165,15 @@ We start by connecting to a LanceDB database path.
If you're using LanceDB Cloud or Enterprise, replace the local connection string
with the appropriate remote URI and authentication details.

<Info>
When you connect to a remote URI (Cloud/Enterprise), `open_table(...)` returns a *remote* table.
Remote tables support core operations (ingest, search, update, delete), but some convenience
methods for bulk data export are not available.

In the Python SDK, `table.to_arrow()` and `table.to_pandas()` are not implemented for remote tables.
To retrieve data, use search queries instead: `table.search(query).limit(n).to_arrow()`.
</Info>

<CodeGroup>
<CodeBlock filename="Python" language="Python" icon="Python">
{PyConnectCloud}
Expand Down Expand Up @@ -450,6 +459,12 @@ You can leverage a full SQL engine like DuckDB to run more complex queries that
sorting, aggregations, joins, etc. To do this, you convert the LanceDB tables to an Arrow table,
which can be natively queried by DuckDB.

<Note>
This workflow applies to local (embedded) tables only. In the Python SDK, remote tables (Cloud/Enterprise)
do not support `to_arrow()` or `to_pandas()`. To retrieve data from remote tables, use search queries
with `.to_arrow()` on the results.
</Note>

<CodeGroup>
```python Python icon="python"
# Convert table to an Arrow table
Expand Down
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