Don’t miss out on Current in New Orleans, October 29-30th — save 30% with code PRM-WEB | Register today
From event-driven architectures to real-time analytics and AI, everything you build starts here.
Data streaming moves high-throughput, low-latency data between systems in real-time. Confluent’s CEO, Jay Kreps, co-created Apache Kafka®—the open source standard for data streaming.
Today, thousands of startups and enterprises trust Confluent instead of managing Kafka. Our cloud-native Kafka engine, KORA autoscales GBps+ workloads 10x faster with 10x lower tail latencies––and a 99.99% SLA.
With data streaming, you don’t operate brittle point-to-point pipelines. Instead, every event—like a click, transaction, sensor reading, or database update—is written to a shared append-only log.
Confluent streams data for any use case:
Optimize your resources at the lowest cost, with pay-as-you-go pricing
Automatically syncs data across global architectures within your private network
Includes RBAC, encryption in transit and at rest, and BYOK
Include SOC 2 Type II, PCI DSS Level 1, HIPAA, and FedRAMP Moderate
Any number of data producers can write events to a shared log, and any number of consumers can read those events independently and in parallel. You can add, evolve, recover, and scale producers or consumers—without dependencies.
Confluent integrates your legacy and modern systems:
Deploy a sample client app in minutes using your preferred language
Avoid 3-6 engineering months of designing, building, and testing each connector
Launch in minutes without operational overhead, reducing your total cost of ownership
Build your own integrations and let us manage the Connect infrastructure
Once events are in the stream, they’re organized into logical topics like "orders" or "payments”. Applications, analytics, and AI all access these topics as a shared source of record.
Confluent enriches your data as it’s created—not after its batched:
Filters, transforms, and joins each event in real-time using SQL
Enforce schema and semantic validation before bad data enters the system
Organizes topics for self-service enrichment and access through a UI or APIs
Represents topics in open table formats such as Apache Iceberg® and Delta Lake