1. Pulsar for Real-time Analytics

A multinational e-commerce company wants to analyze user behavior in real-time to offer instant product recommendations. 

Apache Pulsar’s low-latency messaging ensures that data is processed and analyzed in real-time. Pulsar’s topic-based publish-subscribe model ensures that data is immediately available for analytics, making it ideal for real-time recommendations.

2. Pulsar for IoT Data Collection

An urban development company is deploying thousands of IoT sensors across a city to monitor traffic patterns. 

Pulsar’s ability to handle millions of topics makes it perfect for IoT scenarios. Each sensor can have its own topic, ensuring data integrity and isolation. 

3. Pulsar for Log Data Aggregation

A cloud service provider wants to aggregate logs from thousands of servers to monitor system health. 

Pulsar’s multi-tenancy support means different teams or applications can share a single Pulsar cluster with strong data and processing isolation. This feature, combined with its durability and reliability, makes it a prime choice for log data aggregation.

4. Pulsar for Event Sourcing

A financial institution is building a new transaction system where every transaction is stored as a series of events. 

Pulsar’s guaranteed message delivery and ordering capabilities ensure that every event is captured and processed in the correct sequence. Its storage layer, BookKeeper, ensures data durability, making it a reliable choice for event sourcing. Read about BookKeeper for Pulsar.

5. Pulsar for Data Replication Across Data Centers

A global social media platform wants to replicate user data across multiple data centers around the world. 

Pulsar’s built-in geo-replication feature allows data to be replicated across multiple data centers seamlessly. This ensures data availability and resilience, even if one data center faces issues. Learn about geo-replication with Pulsar.

6. Pulsar for Stream Processing

A weather forecasting agency wants to process vast amounts of meteorological data to predict weather patterns. 

Pulsar integrates seamlessly with popular stream processing frameworks like Apache Flink and Apache Storm. Its native support for complex stream processing tasks, combined with its scalability, makes it a preferred choice for such use cases.

7. Pulsar for Hybrid Cloud Data Streaming

An enterprise is transitioning to a hybrid cloud model and needs to stream data between on-premises infrastructure and cloud platforms. 

Pulsar’s flexibility allows it to be deployed in various environments, including on-premises, cloud, and hybrid setups. Its unified data streaming capabilities ensure smooth data flow across different infrastructures.

8. Pulsar for Financial Transaction Processing

A stock trading platform requires a system to handle millions of trades per second. 

Pulsar’s high-throughput capabilities, combined with its low-latency messaging, ensure that financial transactions are processed quickly and reliably. Its durability guarantees mean that no transaction data is lost.

9. Pulsar for Machine Learning Model Training

A healthcare company is training machine learning models using real-time patient data to predict disease outbreaks. 

The ability of Pulsar to stream large datasets in real-time makes it ideal for ML model training. Its compatibility with popular data processing tools ensures that data scientists can easily integrate it into their ML pipelines.  Learn more about Pulsar functions.

10. Pulsar for Regulatory Compliance and Auditing

A pharmaceutical company needs to maintain a record of all its drug trials for regulatory compliance. 

Pulsar’s immutable data storage ensures that once data is written, it cannot be altered. This, combined with its durability and reliable message delivery, makes it a trusted choice for compliance and auditing use cases.