AI TOOL PROFILE
Unravel Platform: Data Observability and FinOps Software
- Data and Analytics
- Observability Platform
- Enterprise data teams
- Mid-market companies with cloud data estates
- Data Engineering leads
- FinOps practitioners
Pricing
Unravel is free to get started. Paid options are based on monthly consumption of Databricks DBUs, Snowflake warehouses, or BigQuery slots.
At a glance
- Best for
- Enterprise data teams, Mid-market companies with cloud data estates, Data Engineering leads, FinOps practitioners
- Key use cases
- Cloud Cost Reduction, Pipeline Performance Tuning, Data Platform Troubleshooting, Cloud Data Migration
- Integrations
- Databricks, Snowflake, Google Cloud BigQuery, Amazon EMR, Cloudera
- Official website
- Visit unravel platform official website
How AI is used
Unravel is a data observability and FinOps platform designed for teams managing multi-cloud data environments. It monitors data systems to identify bottlenecks and inefficiencies across the technology stack.
The platform supports environments including Databricks, Snowflake, Google Cloud BigQuery, Amazon EMR, and Cloudera. It is designed for data engineering and operations teams in mid-market and enterprise settings.
Unravel uses AI to suggest or implement fixes, such as rewriting Spark jobs or tuning BigQuery slots. This may help teams maintain SLAs and manage cloud spending without requiring deep manual expertise for every optimization.
Buyers should confirm their deployment needs, as the tool offers SaaS, cloud marketplace, and on-premises options. Because pricing is based on consumption metrics, organizations should evaluate their current usage of DBUs, warehouses, or slots to estimate costs.
Key Features
Autonomous Data Optimization
Supports rewriting inefficient Spark jobs, optimizing Snowflake queries, and tuning BigQuery slots.
AI-Driven Root Cause Analysis
Analyzes host metrics, telemetry, and metadata to identify causes of data pipeline inefficiencies.
FinOps Cost Management
Provides chargeback and trend analysis at the workspace, cluster, and user levels.
Multi-Cloud Observability
Supports data systems across AWS, Google Cloud, Azure, and on-premises environments.
Context Graph
A knowledge model that maps signals across workloads, stages, and tasks to connect performance to costs.
Flexible Deployment
Available as a managed SaaS solution, via cloud marketplaces, or as an on-premises deployment within a VPC.
Use Cases
Cloud Cost Reduction
Identifying overspending in Databricks, Snowflake, or BigQuery through rightsizing and idle resource detection.
Pipeline Performance Tuning
Improving the speed of ETL pipelines by rewriting Spark logic and adjusting shuffle and partition strategies.
Data Platform Troubleshooting
Using AI agents to diagnose and fix data pipeline incidents to reduce manual firefighting.
Cloud Data Migration
Supporting the migration of Spark or Hadoop workloads to Databricks with optimization recommendations.
Integrations
- Databricks
- Snowflake
- Google Cloud BigQuery
- Amazon EMR
- Cloudera
- Azure bill integration
FAQ
What does the Unravel platform do?
- Unravel monitors and optimizes data systems across hybrid and multi-cloud environments, using AI to help rewrite code and tune configurations to improve performance and reduce costs.
Which data platforms are supported by Unravel?
- It supports Databricks, Snowflake, Google Cloud BigQuery, Amazon EMR, and Cloudera across AWS, Azure, and Google Cloud.
How is Unravel priced?
- It is free to get started, with paid plans based on the monthly consumption of Databricks DBUs, Snowflake warehouses, or BigQuery slots.
Can Unravel be deployed on-premises?
- Yes, it can be deployed as a managed SaaS, through a cloud marketplace, or as an on-premises installation within a customer VPC.
Source category: Data & Analytics
Source subcategory: Observability Platform
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