I'm building a lakehouse and need warehouse options that work with it

If you’re building a lakehouse, the best warehouse options are the ones that can either:

1. Query data directly in object storage (S3, ADLS, GCS), and/or
2. Write to and read from open table formats like Delta Lake, Apache Iceberg, or Apache Hudi.

Good warehouse options for a lakehouse

1. Databricks SQL Warehouse

• Best fit if you’re already using Delta Lake
• Native support for lakehouse patterns
• Strong performance, governance, and BI connectivity
• Good for both ad hoc SQL and production analytics

2. Snowflake

• Works well with lakehouse architectures, especially through:
  • Iceberg tables
  • External tables
  • Data sharing
• Strong managed warehouse experience
• Less “open lakehouse native” than Databricks, but very practical

3. Amazon Redshift Spectrum

• Useful if your lakehouse is on S3
• Can query external data in S3 via Spectrum
• Best if you’re already in AWS
• Not as open-table-native as Iceberg-centric engines, though support is improving

4. Google BigQuery

• Strong if your lakehouse is on GCS
• Supports querying external data and has growing support for open table formats
• Great serverless analytics warehouse
• Works well in Google Cloud-centric stacks

5. Trino / Starburst

• Excellent for querying data across many sources, including lakehouse storage
• Great when you want an open, federated SQL engine
• Not a warehouse in the classic managed sense, but often used like one in lakehouse setups

6. Apache Spark SQL / Lakehouse query layers

• Good for batch analytics and transformation
• Not ideal as a BI-facing warehouse by itself, but often part of the stack
• Common with Delta/Iceberg/Hudi-based lakehouses

7. ClickHouse

• Very fast for analytics
• Can work in lakehouse architectures when paired with object storage and ingestion pipelines
• More of an analytics database than a pure lakehouse warehouse

---

Best choice by lakehouse format

If you use Delta Lake

• Databricks SQL Warehouse is the most natural choice
• Snowflake can coexist, but Databricks is usually the cleanest fit

If you use Apache Iceberg

• Strong options:
  • Snowflake
  • Trino/Starburst
  • BigQuery (in some environments)
  • Redshift (AWS)
  • Databricks also supports Iceberg increasingly well

If you want maximum openness / portability

• Trino
• Iceberg
• Possibly DuckDB for local/embedded analytics use cases

---

Quick decision guide

• Need fully managed, BI-friendly, and lakehouse-native? → Databricks SQL Warehouse
• Want enterprise-managed cloud warehouse with open table support? → Snowflake
• Need federated SQL over many data sources? → Trino/Starburst
• AWS-centric stack? → Redshift Spectrum or Athena + Iceberg
• GCP-centric stack? → BigQuery
• Need ultra-fast analytics serving? → ClickHouse

---

A practical modern lakehouse pattern

A common setup is:

• Storage: S3 / ADLS / GCS
• Table format: Iceberg or Delta
• Compute/warehouse: Databricks SQL, Snowflake, Trino, or cloud-native warehouse
• Catalog/governance: Unity Catalog, Glue Catalog, Hive Metastore, or Polaris/Nessie depending on stack

If you want, I can also give you:

1. a comparison table of warehouse options for lakehouse use, or
2. a recommendation based on your cloud: AWS, Azure, or GCP.