BigQuery and Dataproc to Databricks on Google Cloud

Run Databricks on Google Cloud next to your data, and bring analytics, engineering and ML onto one platform.

By NeuralShore EngineeringPublished October 14, 20261 min read

Cover illustration: BigQuery and Dataproc to Databricks on Google Cloud

Short answer

Databricks runs on Google Cloud, so teams can move BigQuery, Dataproc and Dataflow workloads next to their data and unify SQL, Spark, streaming and ML with open table formats and one governance model. Start with one business domain end to end to prove the pattern before moving the rest.

Key takeaways

Data stays in your Google Cloud project.
Open formats reduce engine lock-in.
Migrate one domain end to end first.

Google Cloud customers often split work between BigQuery for analytics and Dataproc for Spark processing. Data science may happen somewhere else again.

Why teams consider Databricks

One platform for SQL, Spark, streaming and ML.
Open table formats that any engine can read.
Unified governance for data, models and agents.
Built-in Genie and Agent Bricks on governed data.

Staying on Google Cloud

Databricks runs on Google Cloud, so data does not need to leave your cloud. We deploy close to existing storage to keep transfer simple.

How we migrate

Inventory BigQuery datasets, scheduled queries and Dataproc jobs.
Convert SQL and move Spark jobs.
Rebuild Dataflow and scheduled logic as declarative pipelines.
Reconcile results with report owners before cut-over.

A practical tip

Migrate one business domain end to end first, such as customer or finance. It proves the pattern and gives users a complete experience.

About the author

NeuralShore Engineering, Databricks delivery team

Databricks architects, data engineers and AI engineers at NeuralShore, DLytica’s Databricks delivery company. Leadership comes from IBM data and AI architecture.