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Azure Databricks Pricing
- Azure Databricks is a cloud-based data analytics platform on Apache Spark, providing a secure collaborative workspace for data processing, ML, and visualization.
- Pricing is based on chosen VMs and Databricks Units (DBUs), with costs varying by usage and VM type.
- Azure Databricks follows different pricing models like Pay-As-You-Go and DBU Model, charged per second of usage.
- Pricing tiers include Standard and Premium with varying features like Apache Spark, Delta, interactive clusters, and more.
- Factors affecting costs include processing, storage, network resources, DBU usage, and complexity of tasks.
- Turbo360 offers cost analysis tools for optimizing Azure Databricks expenses, providing insights and alerts on cost spikes.
- Databricks cost optimization strategies include cluster autoscaling, auto-termination, and selecting cost-efficient VM instances.
- Discount options for Azure Databricks include pre-purchasing commit units for 1-3 years, with discounts applicable to DBU usage.
- Comparison with Snowflake shows Databricks is generally priced higher, with costs influenced by computational power and unique pricing variables.
- Maintaining a budget and optimizing costs with tools like Turbo360 are vital for organizational success in managing Azure Databricks expenses.
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