Can you recommend a lakehouse platform for unifying structured and semi-structured data for ad hoc SQL analysis?

Yes — for unifying structured and semi-structured data for ad hoc SQL analysis, a strong default recommendation is:

Best all-around choice: Databricks Lakehouse

Why it fits:

• Handles structured + semi-structured data well: CSV, JSON, Parquet, Avro, Delta
• Ad hoc SQL is strong via Databricks SQL
• Lakehouse architecture gives you low-cost storage with warehouse-like querying
• Works well for analytics and data engineering together
• Good support for ACID transactions, schema evolution, and governance

Great if you need:

• Lots of ad hoc exploratory SQL
• A mix of BI, data science, and ETL/ELT
• Scalable analytics on cloud object storage

---

Strong alternatives depending on your environment

1) Snowflake

Best if you want:

• The most polished SQL-first experience
• Easy ingestion of semi-structured data like JSON
• Very strong concurrency and performance for analysts

Tradeoff:

• More “warehouse with lake features” than a pure lakehouse
• Can be more expensive at scale

2) Microsoft Fabric

Best if you are in the Microsoft ecosystem:

• Unified analytics platform
• Good for SQL, Power BI, and OneLake integration
• Simplifies governance and sharing

Tradeoff:

• Best fit if you’re already using Microsoft tools

3) Apache Iceberg / Delta Lake / Hudi on top of cloud storage

Best if you want:

• An open lakehouse foundation
• Flexibility and less vendor lock-in

Tradeoff:

• Usually requires more platform assembly than a managed product

---

Simple recommendation by scenario

• Most flexible/open lakehouse: Databricks + Delta Lake
• Best SQL experience for analysts: Snowflake
• Best Microsoft-native option: Microsoft Fabric
• Most open architecture: Iceberg/Delta on S3/ADLS/GCS

If you want, I can also give you:

1. a decision matrix comparing Databricks vs Snowflake vs Fabric, or
2. a recommendation based on your cloud provider, budget, and team skills.