Turntable.so: Collaborative AI-Powered Data Product Development

Turntable.so is a powerful AI-powered collaborative workspace designed for teams to develop, deploy, and monitor data products with ease. Built for data engineers, analysts, and teams working with complex data stacks, Turntable.so combines advanced data transformation tools with a purpose-built code editor and AI assistance to streamline data modeling, documentation, and profiling. Backed by Y Combinator, it supports SQL, dbt Core, and SQLMesh, enabling seamless integration with platforms like Snowflake. With features such as column-level lineage, multiplayer projects, virtual data branches, and end-to-end monitoring with alerts and data diffs, Turntable.so delivers full visibility into data operations. Its native AI assistant enhances productivity by offering intelligent suggestions and insights throughout the data lifecycle.

Key Features:

• AI-Powered Collaboration: A native AI assistant that supports data modeling, documentation, and profiling.
• Code Editor: Purpose-built for data transformation with support for SQL, dbt Core, and SQLMesh.
• Column-Level Lineage: Track data flow and dependencies across transformations.
• Multiplayer Projects: Real-time collaboration among team members.
• Automated Catalog: Automatically generates and maintains a centralized data catalog.
• Virtual Data Branches: Create isolated environments for testing and development.
• Monitoring & Alerts: End-to-end visibility with real-time monitoring and alerting.
• Data Diff: Compare data across versions to identify changes and inconsistencies.
• Tool Integrations: Seamless integration with Snowflake and other data platforms.

Pricing: Turntable.so offers a 14-day free trial with no credit card required, making it accessible for teams to explore its capabilities before committing.

Conclusion: Turntable.so is a cutting-edge platform that empowers data teams to work smarter with AI-driven collaboration and robust data management tools, delivering efficiency, transparency, and scalability in every stage of data product development.