Snowflake Alternatives for Startups 2026 скачать в хорошем качестве

Snowflake Alternatives for Startups 2026

Snowflake alternatives: which data warehouse should you actually use in 2026? In this video, I break down the three biggest Snowflake alternatives (Google BigQuery, Amazon Redshift, and Databricks), covering what each one does well, where they fall short, and what they actually cost. Then I'll show you why most startups don't need any of these enterprise platforms, and demonstrate a simpler alternative that gets you from zero to analytics in under 30 minutes. 🔗 Try Definite free: https://ui.definite.app 📚 Definite docs: https://docs.definite.app 💰 Pricing: https://www.definite.app/pricing ⏱️ CHAPTERS: 0:00 Introduction 0:37 Why people look for Snowflake alternatives 1:18 Google BigQuery breakdown 2:14 Amazon Redshift breakdown 3:12 Databricks breakdown 4:02 Head-to-head comparison 4:31 The real problem: you still need more tools 5:35 If you're a startup, you probably don't need any of these 5:37 Definite: all-in-one data platform 6:04 Live demo: connecting data and using Fi 7:23 When to use enterprise options vs Definite 8:15 Final thoughts 📊 WHAT YOU'LL LEARN: • Why Snowflake's consumption-based pricing gets unpredictable • How BigQuery, Redshift, and Databricks compare on cost and features • Which cloud lock-in each platform requires • Why all four platforms still need additional tools bolted on • The total cost of a modern data stack ($5,000-$25,000/month) • A simpler alternative for startups that need analytics now 🔍 QUICK COMPARISON: Snowflake: • Great for SQL analytics • Unpredictable consumption-based pricing • Works across clouds • Has Snowpark, Cortex for AI BigQuery: • Serverless, pay-per-query • Google Cloud only • BigQuery ML, Vertex AI integration • Zero infrastructure management Redshift: • AWS-native, predictable pricing with reserved instances • Cluster-based architecture • Redshift ML, Spectrum for S3 queries • Serverless option available Databricks: • Lakehouse architecture (data lake + warehouse) • Best for ML and data engineering • Truly multi-cloud (AWS, Azure, GCP) • Complex, steep learning curve • $50,000-$200,000+/year for moderate usage All four require: • ETL tools (Fivetran, Airbyte) • Transformation layer (dbt, Dataform) • BI tools (Looker, Tableau, Power BI) • Data engineering team • $5,000-$25,000+/month total stack cost Definite: • All-in-one platform (warehouse, ETL, semantic layer, dashboards, AI assistant) • Setup in under 30 minutes • 500+ pre-built connectors • No data team required • One platform, one bill 👥 WHO IS THIS FOR: • Startup founders evaluating data warehouse options • Data leaders comparing Snowflake alternatives • Teams tired of managing 4-5 different data tools • Anyone who wants analytics without hiring a data engineer • Companies looking to reduce their data stack costs 🔗 LINKS: • Definite: https://www.definite.app • Fi (AI Assistant): https://www.definite.app/fi • 500+ Connectors: https://www.definite.app/connector-db • Stripe connector: https://www.definite.app/connector/st... • HubSpot connector: https://www.definite.app/connector/hu... #Snowflake #BigQuery #Redshift #Databricks #DataWarehouse #SnowflakeAlternatives #DataEngineering #Analytics #Startups #DataPlatform #BI #CloudData