The Beeks Core Data Feed streaming interface provides decentralized capture and centralized processing, significantly enhancing scalability and flexibility.
Benefits
Decentralized Capture with Centralized Processing
Beeks’ system captures data at a single point and transmits it to a centralized analytics server, reducing infrastructure overhead.Scalability
A single Core Data Feed can handle multiple data streams without requiring additional appliances or independent analytics streams, making it horizontally scalable.Customizable and Efficient Data Delivery
Beeks CDF allows users to configure what specific metrics or decoded messages they need, reducing noise and improving efficiency.Lower Risk Exposure
The centralized model reduces the need for continuous monitoring of multiple streams, lowering the risk of missing critical trading data due to a stream failure.
Summary
Feature | Beeks Analytics |
|---|---|
Architecture | Centralized Core Data Feed with decentralized capture. |
Scalability | One Core Data Feed handles multiple streams, enabling horizontal scalability. Utilizes Kafka partitions for near-linear horizontal scaling to handle hundreds of millions of messages per second. |
Operational Complexity | Lower – single data source with customizable feeds. |
Integration & Ecosystem | Standard Kafka topics easily feed Spark, Flink, BI tools, Big Data and AI/ML pipelines. |
Data Pipeline Flexibility | Highly configurable publish/subscribe model with user-defined topics and filters. |
Time to Insight | Low-latency feed directly into analytics or AI via Kafka; minimal extra overhead. |
Cost & Overhead | Commodity servers + open-source Kafka reduce TCO; seamless scale without re-buying appliances. |
Failure Risk | Lower – centralized processing reduces dependency on multiple streams. Kafka replication ensures data integrity even if broker nodes fail. Centralized analytics with decentralized capture plus Kafka’s fault tolerance reduce risk. |