Tecton
Enterprise feature platform for real-time machine learning
Tecton is profiled here as a LLM tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Tecton is an enterprise feature platform founded in 2019 by Mike Del Balso, Kevin Stumpf, and Jeremy Hermann, the team behind Uber's Michelangelo ML platform, and acquired by Databricks in 2025. It defines batch, streaming, and real-time feature pipelines declaratively in Python, then computes, stores, and serves the results with single-digit-millisecond latency for fraud detection, recommendations, and agent context. Inside Databricks, Tecton's serving layer connects real-time context to Agent Bricks and the wider Data Intelligence Platform.
Key Capabilities:
Declarative Python framework for batch, streaming, and real-time features
Rift compute engine for feature transformation without Spark cluster management
Low-latency online serving with offline-online consistency
Streaming aggregations over event data
Feature versioning, lineage, and access governance
Real-time context serving for ML models and AI agents
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