Useful Data Tips

Snowflake

⏱️ 8 sec read 🗄️ Data Management

What it is: Cloud data warehouse. Auto-scaling, pay-per-use, separation of storage and compute.

What It Does Best

Scale without thinking. Query performance stays consistent. Add compute instantly, remove when done.

Multi-cloud. Runs on AWS, Azure, GCP. Same SQL, same features everywhere.

Zero maintenance. No servers to manage. No tuning. No indexes. Just write SQL.

Key Features

Separation of storage and compute: Scale independently, pause compute when not in use

Virtual warehouses: Multiple isolated compute clusters

Zero-copy cloning: Instant database copies for dev/test

Time Travel: Query historical data up to 90 days back

Data sharing: Share live data across accounts securely

Pricing

On-demand: $2-4/credit-hour (compute) + $23-40/TB/month (storage)

Pre-purchase: Discounts with upfront credit purchase

Typical cost: $200-2,000/month for small teams, $10k+/month for heavy users

Free trial: $400 credits to start

When to Use It

✅ Analytics on large datasets (TB+)

✅ Variable workload (scale up/down)

✅ Multiple teams needing different compute

✅ Don't want to manage infrastructure

✅ Need data sharing across organizations

When NOT to Use It

❌ Transactional database needs (use Postgres)

❌ Small datasets (< 100GB, Postgres cheaper)

❌ Need sub-second query response (not optimized for OLTP)

❌ Budget very tight (can get expensive)

❌ Heavy real-time streaming (use specialized tools)

Common Use Cases

Data warehouse: Central repository for business analytics

BI dashboards: Power Tableau, Looker, Power BI

Data science: Large-scale data preparation for ML

Data sharing: Share data with partners/customers

ELT pipelines: Load and transform data at scale

Snowflake vs Alternatives

vs BigQuery: Snowflake multi-cloud, BigQuery tighter Google integration

vs Redshift: Snowflake easier and often faster, Redshift cheaper on AWS

vs Databricks: Databricks better for ML/Spark, Snowflake better for SQL analytics

Unique Strengths

True multi-cloud: Same experience on AWS, Azure, GCP

Compute isolation: Workloads never interfere with each other

Zero-copy clone: Instant environments without data duplication

Data marketplace: Access to third-party data sets

Bottom line: Data warehouse made easy. Expensive for small use, but scales painlessly. If you're drowning in data and query performance, Snowflake solves it.

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