Currently the main benefit of BigLake over the current external tables is governance: you get row and column level security over cloud storage data. The governance is uniformly enforced across BigQuery and also the BigQuery storage API. The storage API can be used by any engine and we have pre-built open source connectors available for Spark, Presto/Trino, Dataflow and Tensorflow.
We're constantly working on improving BigQuery performance over open file formats on cloud storage. Some of these features will be specific to BigLake. Please stay tuned.
I work on BigQuery. All of these are great points: just wanted to point out that BigQuery can federate into external data sources as well: e.g. files on cloud storage and BigTable. Relevant feature is BigLake: https://cloud.google.com/bigquery/docs/biglake-intro
BigQuery also supports in-place querying of datasets on GCS (or S3/Azure using Omni) via external/BigLake tables. https://cloud.google.com/bigquery/docs/query-cloud-storage-u...