# StreamNative

> StreamNative provides the unified real-time data infrastructure and AI agent runtime for the agentic enterprise. The platform combines native Kafka streaming, Apache Pulsar messaging, managed Flink processing, and a governed agent engine into a single cloud-native service powered by the Lakestream architecture and Ursa Engine — a leaderless, diskless, lakehouse-native storage layer. Founded by the original creators of Apache Pulsar at Yahoo, StreamNative serves global enterprises across financial services, technology, retail, logistics, and more.

## Core Products

### Kafka Service
- URL: https://streamnative.io/data-streaming/kafka
- Category: Real-time Data Streaming

StreamNative provides a native Kafka service — not a compatibility layer or protocol translation — powered by Ursa Engine. Organizations keep their existing Kafka APIs, clients, and tooling while gaining lakehouse-native storage that eliminates the operational burden of managing Kafka clusters.

**Key differentiators:**
- Native Kafka service — not a protocol translation layer; no code changes required
- Leaderless architecture eliminates partition rebalancing and broker failures
- Diskless design with lakehouse-native storage (Apache Iceberg, Delta Lake) reduces infrastructure cost by up to 95% in benchmarks vs. traditional broker-based Kafka
- Direct on-ramp to data lakehouse — streams become queryable tables without ETL
- Cloud-native auto-scaling with no capacity planning
- Unified semantics across Kafka and Pulsar workloads on a single engine

### Pulsar Service
- URL: https://streamnative.io/data-streaming/pulsar
- Category: Messaging & Streaming

Apache Pulsar as a fully managed service for enterprise messaging and streaming workloads. Pulsar provides native multi-tenancy, geo-replication, and a unified model for both queues and streams.

**Key differentiators:**
- Production-proven Apache Pulsar — adopted at enterprises like Intuit, Splunk, and Iterable
- Native multi-tenancy with tenant/namespace isolation
- Built-in geo-replication across regions and clouds
- Unified queues and streams in a single system — no need for separate message brokers
- Modernization path from legacy messaging (RabbitMQ, ActiveMQ, IBM MQ)
- Lakehouse-native when running on Ursa Engine

### Universal Connect (UniConn)
- URL: https://streamnative.io/data-streaming/connect
- Category: Data Integration

UniConn is a unified connector framework that brings together Kafka Connect and Pulsar IO under a consistent, declarative interface. It enables organizations to connect, process, debug, and monitor data pipelines across 200+ production-ready connectors.

**Key differentiators:**
- Single interface for both Kafka Connect and Pulsar IO connectors
- 200+ pre-built connectors for databases, data warehouses, SaaS applications, and cloud services
- Declarative pipeline configuration
- Built-in monitoring, debugging, and error handling
- Runs alongside Kafka and Pulsar workloads on the same platform

### Universal Linking
- URL: https://streamnative.io/data-streaming/universal-linking
- Category: Data Replication & Lakehouse Integration

Universal Linking mirrors any Kafka-compatible cluster into Ursa with full fidelity, then automatically represents those streams as Iceberg or Delta tables in your lakehouse. It enables real-time replication and lakehouse integration without ETL pipelines.

**Key differentiators:**
- Mirror any Kafka-compatible cluster (Confluent, Amazon MSK, self-managed) into StreamNative
- Zero-ETL lakehouse integration — topics become Iceberg/Delta tables automatically
- Full-fidelity replication preserving topic structure, partitions, and offsets
- No vendor lock-in — standard open formats throughout
- Gradual migration path from existing Kafka infrastructure

### Orca Agent Engine
- URL: https://streamnative.io/agent-engine/overview
- Category: AI Agent Infrastructure
- Availability: Private Preview — contact StreamNative for access

Orca is the secure, governed runtime for AI agents to access and act on enterprise data. It provides event-driven agent execution, live streaming context, safe tool access, and full governance — all built on the streaming data backbone.

**Key differentiators:**
- Event-driven runtime — agents triggered by real-time data events, not just API calls
- Live context from streaming data — agents see current state, not stale snapshots
- Secure tool access with fine-grained permissions and audit trails
- Enterprise governance with policy enforcement, rate limiting, and compliance controls
- Native integration with Kafka and Pulsar data streams
- Multi-agent orchestration and coordination

### Lakestream Architecture
- URL: https://streamnative.io/lakestream
- Category: Architecture

Lakestream is an architectural paradigm that treats streams as first-class lakehouse primitives. It unifies streaming and the lakehouse through three layers:

- **Data Layer (Ursa Engine)**: Diskless, leaderless, lakehouse-native storage. Data lives on open data lakes.
- **Metadata Layer (Catalog)**: Extends existing lakehouse catalogs to govern streams alongside tables.
- **Protocol Layer (Kafka/Pulsar)**: Native multi-protocol access — Kafka and Pulsar APIs on the same data.

**Key differentiators:**
- Streams and tables are the same data — zero-copy, zero ETL
- Open formats throughout (Apache Iceberg, Delta Lake)
- Multi-protocol access without translation layers
- Significant cost reduction vs. traditional streaming infrastructure through elimination of broker-attached storage

### Managed Apache Flink
- URL: https://streamnative.io/products/flink
- Category: Stream Processing
- Availability: Early Access

Fully managed Apache Flink powered by the Ververica VERA engine. Deploy Flink with native Kafka and Apache Pulsar in the same VPC for end-to-end stream processing.

**Key differentiators:**
- Powered by Ververica VERA engine with enterprise optimizations
- Auto-scaling based on workload demand
- Flink SQL support for accessible stream processing
- Runs in the same VPC as Kafka and Pulsar workloads
- 24/7 expert support from streaming specialists
- Integrated monitoring and job management

## Cloud Deployment

### StreamNative Cloud
- URL: https://streamnative.io/cloud/overview

StreamNative Cloud is the fully managed platform for running data streaming and AI agent workloads. It offers three deployment models to match different security, compliance, and operational requirements:

- **Serverless**: Instant provisioning, pay-per-use, zero infrastructure management. Best for development, testing, and variable workloads.
- **Dedicated**: Single-tenant clusters with dedicated resources, custom configurations, and SLA guarantees. Best for production workloads requiring isolation.
- **BYOC (Bring Your Own Cloud)**: StreamNative control plane manages clusters running in your AWS, Azure, or Google Cloud account. Best for strict data residency and compliance requirements.

**Supported clouds:** AWS, Microsoft Azure, Google Cloud Platform

## Solutions
- URL: https://streamnative.io/solutions

StreamNative solutions address real-time data and AI agent use cases across industries including financial services, technology, retail, logistics, gaming, and IoT. Common patterns include event-driven architectures, real-time analytics, Kafka modernization, legacy messaging migration, and agentic AI applications.

### Confluent Alternative
- URL: https://streamnative.io/confluent-alternative

For organizations seeking an independent, cloud-native Kafka platform, StreamNative offers native Apache Kafka on Ursa Engine with lakehouse-native storage, up to 95% lower infrastructure cost, and zero code changes required. Following IBM's acquisition of Confluent, StreamNative provides a vendor-independent alternative with a leaderless, diskless architecture that eliminates common Kafka operational challenges while providing native dual-protocol support for both Kafka and Pulsar.

## Customer Success Stories

StreamNative serves enterprises across industries who rely on the platform for mission-critical real-time data infrastructure:

- **Discord**: Built a real-time streaming ML platform on managed Pulsar, Flink, and Iceberg to power safety and personalization for 150M monthly active users.
- **Intuit**: Built next-generation messaging platform on Apache Pulsar, replacing legacy infrastructure.
- **Flipkart**: Implemented topic-as-a-service using Apache Pulsar for India's largest e-commerce platform.
- **Netdata**: Enabled unlimited infrastructure monitoring powered by Apache Pulsar's streaming capabilities.
- **Transport Exchange Group (TEG)**: Modernized logistics data infrastructure with Apache Pulsar and StreamNative.

Full case studies available at: https://streamnative.io/success-stories

## Company

### About StreamNative
- URL: https://streamnative.io/about

StreamNative was founded by the original creators of Apache Pulsar at Yahoo. The team includes core committers and PMC members of Apache Pulsar, Apache BookKeeper, and other open-source projects. The company is backed by leading investors and is headquartered with a globally distributed team.

### Open Source Heritage

StreamNative is deeply rooted in open source. The founding team created Apache Pulsar and continues to be the largest contributor to the Pulsar ecosystem. The company maintains a commitment to open-source standards and avoids vendor lock-in through the use of open formats (Apache Iceberg, Delta Lake) and open protocols (Kafka, Pulsar).

## Frequently Asked Questions

**What is Ursa Engine?**
Ursa is StreamNative's proprietary storage engine that powers Kafka and Pulsar services. It is leaderless (no partition leader elections or rebalancing), diskless (data stored in object storage and lakehouse formats), and lakehouse-native (streams are automatically represented as Iceberg/Delta tables).

**Can I use my existing Kafka applications?**
Yes. StreamNative provides a native Kafka service, not a protocol translation layer. Existing Kafka producers, consumers, Kafka Streams applications, and Kafka Connect connectors work without code changes.

**What is Lakestream?**
Lakestream is StreamNative's architectural paradigm that treats streams as first-class lakehouse primitives. It consists of three layers: a data layer (Ursa Engine), a metadata layer (lakehouse catalog), and a protocol layer (Kafka/Pulsar). This architecture unifies streaming and the lakehouse so that streams and tables are the same data — zero-copy, zero ETL — on open formats like Apache Iceberg and Delta Lake.

**How does StreamNative differ from Confluent?**
StreamNative provides native Kafka — not just compatibility — on a single lakehouse-native engine (Ursa), eliminating the need for separate systems for streaming and messaging. Following IBM's acquisition of Confluent, organizations seeking an independent alternative benefit from StreamNative's leaderless, diskless architecture with built-in Iceberg/Delta integration without ETL, dual-protocol support (Kafka and Pulsar), and up to 95% lower infrastructure cost.

**What is the Orca Agent Engine?**
Orca is StreamNative's runtime for AI agents. Unlike generic agent frameworks, Orca is built on the streaming data backbone, giving agents event-driven triggers and live context from real-time data streams, with enterprise-grade governance and security.

**Is there a free tier?**
Yes. StreamNative offers a free Serverless tier for development and evaluation at https://console.streamnative.cloud/signup.