Unravel’s purpose-built AI for Snowflake enables data observability and FinOps insights based on Unravel’s granular visibility at the warehouse, user, and SQL query level. Unravel’s AI-driven recommendations enable Snowflake users to run 50% more workloads on their existing warehouses, achieve ±10% cloud data budget forecast accuracy, simplify troubleshooting to meet 99%+ SLAs, and boost reliability to launch new cloud data applications 3x faster. With Unravel, Snowflake users can speed data analytics initiatives with granular and real-time cost visibility, predictive spend forecasting, and performance insights for their data cloud.
Unravel’s AI-powered Insights Engine understands all the intricacies and complexities of Snowflake and the supporting infrastructure to optimize efficiency and performance.
Unravel for Snowflake provides a single source of truth to improve collaboration across functional teams and accelerates workflows for common use cases. Below are just a few examples of how Unravel helps Snowflake users for specific situations.
Scenario: Understand what we pay for Snowflake down to the user/app level in real time, accurately forecast future spend with confidence.
Benefits: Granular visibility at the warehouse, query, and user level enables FinOps practitioners to perform cost allocation, estimate annual data cloud application costs, cost drivers, break-even, and ROI analysis.
Scenario: Identify the most impactful recommendations to optimize overall cost and performance.
Benefits: AI-powered performance and cost optimization recommendations enable FinOps and data teams to rapidly upskill team members, implement cost efficiency SLAs, and optimize Snowflake pricing tier usage to maximize the company’s cloud data ROI.
Scenario: Identify the most impactful recommendations to optimize the cost and performance of a warehouse.
Benefits: AI-driven insights and recommendations enable product and data teams to improve credit utilization, boost SQL query performance, leverage table partitioning and column clustering to achieve cost efficiency SLAs and launch more data queries within the same warehouse budget.
Scenario: Live monitoring with alerts.
Benefits: Live monitoring with alerts speed mean time to repair (MTTR) and prevent outages before they happen.
Scenario: Debugging a query and comparing queries.
Benefits: Automatic troubleshooting guides data teams directly to the pinpoint source of query failures down to the line of code or SQL query along with AI recommendations to fix it and prevent future issues.
Scenario: Identify expensive, inefficient, or failed queries.
Benefits: Proactively improve cost efficiency, performance, and reliability before deploying queries into production. Compare two queries side-by-side to find any metrics that are different between the two runs, even if the queries are different.
Yes. Snowflake pricing is based on virtual warehouse (compute) size, cloud services, data storage, and other factors. Compute usage is billed on a per-second basis (minimum of 60 seconds). You can also pre-purchased Snowflake capacity to reduce processing costs. Estimate Snowflake costs online with the Snowflake business value calculator.
Yes. Unravel helps you allocate, track, and manage costs with pinpoint precision. Unravel helps you break down and allocate costs by department, team, workload, application, even down to the individual job or user level.
Unravel provides granular Insights, recommendations, and automation for before, during and after your Spark, Hadoop and data migration to Snowflake. Unravel for Snowflake is a complete data observability platform to help you tune, troubleshoot, cost-optimize, and ensure data quality on Snowflake. Unravel provides AI-powered recommendations and automated actions to enable intelligent optimization of data pipelines and data applications.