I'm building a customer analytics platform and need a warehouse recommendation

For a customer analytics platform, the best warehouse choice depends on your data shape, concurrency, freshness needs, and team skills. If you want a practical default recommendation:

My default recommendation

Snowflake is usually the safest choice for customer analytics platforms because it offers:

• Easy scalability for both storage and compute
• Strong support for semi-structured data
• Good performance for mixed workloads
• Simpler operations than self-managed systems
• Wide ecosystem support

When I’d recommend something else

Choose BigQuery if:

• You’re already on Google Cloud
• You want minimal warehouse administration
• Your workload is mostly ad hoc analytics and ELT
• You expect large, bursty queries rather than constant heavy concurrency

Choose Redshift if:

• You’re heavily invested in AWS
• You want tighter integration with the AWS ecosystem
• Your team is comfortable tuning warehouse performance
• Cost control at scale is a major priority and you can manage some ops overhead

Choose Databricks / Lakehouse if:

• You’re doing a lot of ML, feature engineering, or streaming
• You need one platform for analytics + data science + pipelines
• Your data is more “data lake first” than warehouse first

What matters most for customer analytics

For customer analytics, the most important requirements are usually:

• Fast SQL on large event data
• High concurrency for dashboards and analysts
• Near-real-time ingestion
• Support for identity resolution / customer 360
• Flexible handling of clickstream, event, and profile data

Snowflake tends to fit these well out of the box.

Short recommendation by scenario

• Best overall: Snowflake
• Best for GCP: BigQuery
• Best for AWS-native teams: Redshift
• Best for ML-heavy / lakehouse architecture: Databricks

If you want, I can narrow it down further

If you tell me:

1. Cloud provider
2. Data volume per day
3. Number of analysts/dashboard users
4. Whether you need real-time or batch
5. Budget sensitivity

…I can give you a much more specific recommendation.