Lightning Tables is a managed serving layer that durably stores and materializes Apache Kafka® data into tables, keeping business state current as changes arrive – instantly queryable for agents, applications, and analytics.
Data freshness of <100ms from data creation to serving
One plane of governance across capturing changes to serving agents
Schema evolution prevents breaking downstream applications
Understand what’s happening in the business now. Query in milliseconds. No extra database. No reverse-ETL.
Lightning Tables is a high-performance, read-only serving layer built on Kafka. It materializes topics into their own durable and real-time indexed storage, so data stays queryable well past Kafka's retention window.
It maintains the current state of your business for AI and operational workloads, giving you a first-party way to serve fresh, continuously updated data directly from Confluent Cloud.
Introducing Lightning Tables
Read about the new Query pillar and Lightning Tables, now generally available.
Get Started using the Quickstart
Turn on Lightning Tables for your topics and serve context for agents, do fraud detection, and more.
Data freshness ensures 100ms from new data creation to serving, with 10-100ms response time and throughput of 1000+ QPS. Use Lightning Tables as a feature store, computing features in Flink and storing them for ML use cases such as real-time personalization.
Enable Lightning Tables on Kafka topics to create a real-time index and always-current serving layer in Confluent Cloud – no ETL pipelines, extra databases, or caches. Access data in Lightning Tables using MCP, SQL, or direct API.
Close the gap between live signals and when agents know about it. Serve trustworthy context for agents to act on the current state of the business instead of stale snapshots – improving relevance, responsiveness, and decision quality.
Serve high-quality data to your existing systems on day one. No rip and replace. Keep your current applications and downstream services while Lightning Tables gives them a fast path to fresh operational data.
Data in Lightning Tables power very different uses at once, each in the form it needs. Below are four examples, one set of data, and no separate pipeline or copy for any of them.
A live dashboard shows dispatchers what's happening with every driver in the field right now, querying the data with SQL and using ML for predictive maintenance.
The routing system subscribes to the recommendation stream and reassigns drivers and deliveries automatically as conditions change.
Background agents evaluate delivery progress alongside live truck and route conditions to identify shipments at risk of delay or vehicles that may need attention.
An agent lets dispatchers ask questions in plain language, such as which trucks are most likely to break down today, and answers from live context over MCP through the Real-Time Context Engine.
Neue Entwickler erhalten Credits im Wert von 400 $ für die ersten 30 Tage – kein Kontakt zum Vertrieb erforderlich.
Confluent bietet alles Notwendige zum: – Entwickeln mit Client-Libraries für Sprachen wie Java und Python, Code-Beispielen, über 150 vorgefertigten Connectors und einer Visual Studio Code-Extension. – Lernen mit On-Demand-Kursen, Zertifizierungen und einer globalen Experten-Community. – Betreiben mithilfe einer CLI, IaC-Unterstützung für Terraform und Pulumi und OpenTelemetry-Observability.
Die Registrierung ist über das Cloud-Marketplace-Konto unten möglich oder direkt bei uns.

