Ursa vs. Kafka

Apache Kafka® compatibility without the Kafka complexity. Discover how StreamNative URSA delivers superior performance, 10x lower costs, and enhanced flexibility for AI workloads compared to Kafka. Learn why companies are choosing StreamNative Ursa over Kafka to power mission-critical data streams with confidence.

Key Advantages of StreamNative Ursa over Kafka

Cloud-Optimized Leaderless Architecture

StreamNative

StreamNative’s leaderless architecture dramatically reduces the cost of Kafka. Any node can accept writes and independently store them in a shared object storage service. This eliminates the inter-zone client traffic.

Kafka

Kafka’s traditional architecture tightly couples storage and compute, requiring resources to scale together, leading to inefficiency and excessive cloud costs.

Elastic and Cost-Efficient Scaling

StreamNative

With its leaderless architecture, StreamNative can run 5GB of Kafka workloads in just $54 per hour which is 85% lower than self-managed kafka and other fully managed Kafka vendors like AWS MSK and Redpanda.

Kafka

Kafka’s architecture requires manual scaling and complex resource management, resulting in higher operational costs and potential downtime.

Lakehouse-Native Storage

StreamNative

StreamNative offers seamless integration with ecosystem components, including lakehouse storage, Databricks Unity Catalog and Snowflake Open Catalog. This integration provides users with a unified solution that enables both operational data processing and advanced analytics within the same platform, lowering storage costs while expanding data governance capabilities.

Kafka

Kafka doesn’t natively support lakehouse or similar integrated storage solutions, typically requiring external components for full integration.

Migration from Kafka to StreamNative with UniLink

StreamNative Ursa engine supports Kafka’s native API, allowing businesses to migrate existing Kafka applications without code changes. With StreamNative’s UniLink, cost-effective solution for data replication, can help you to migrate self-managed or fully-managed Kafka to StreamNative seamlessly.

Why Consider StreamNative?

Future-proofing

StreamNative’s leaderless and lakehouse-native storage …

10x Lower TCO

StreamNative’s leaderless architecture reduces infrastructure costs and simplifies scaling, providing a more cost-effective solution, especially in building end-to-end data pipelines with lakehouses.

Kafka Compatibility

StreamNative allows seamless migration from Kafka, providing organizations with a smooth transition to its more flexible, efficient, and scalable platform.

Exceptional Performance & Scale

With StreamNative Ursa, experience …

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StreamNative vs Kafka

Features Comparison

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Kafka

Feature Comparison: Scalability vs. Stability

Efficent operations

Scalability refers to the system's ability to grow and manage increased demand without performance loss. A scalable system can adapt to changing needs, making it future-proof.

Stability ensures that the system operates reliably under various conditions. A stable system minimizes downtime and provides a consistent user experience, which is critical for business operations.

Feature Comparison: Customization vs. Standardization

Efficent operations

Customization allows users to tailor their experience according to personal preferences, enhancing satisfaction and engagement. However, it can lead to complexity in system management.

Standardization simplifies processes and ensures consistency across platforms. While it may limit personalization, it enhances compatibility and reduces training time for new users.