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Process High-Volume Datasets with Apex Cursors
Learn how to migrate from Batch Apex to Cursors to manage high-volume datasets. Explore benchmark performance, compare serialization approaches, and identify best practices.

, Salesforce Developer, Nortal

, Salesforce Studio Lead, Nortal

Product: Salesforce Platform
Role: Developer
Industry: Technology
Topic: Productivity
Session Level: Intermediate
Session Format: Theater
  • Tuesday, Sep 153:00 PM - 3:20 PM PDT
    (10:00 PM - 10:20 PM GMT)
    Moscone West, L1 Forest, Developer Grove
    FIRST COME FIRST SEATED
Session Summary: The session provided an in-depth analysis of asynchronous and synchronous processing in Salesforce, focusing on Apex and its mechanisms for managing background processing. It highlighted the benefits and limitations of tools such as future methods, batch Apex, and Apex cursors, with a particular emphasis on the scalability and control offered by cursors for handling large data volumes, up to 50 million rows. A live demonstration compared the performance of batch Apex and cursors, illustrating how each performs under different scenarios, such as light and heavy processing loads, with cursors excelling in scenarios requiring state preservation and fewer transactions. Attendees were also guided on when to use batch Apex versus Apex cursors, emphasizing considerations like transaction counts, control requirements, and record volume, alongside a recommendation to leverage AI tools for process migration in the AI-first era of Salesforce development.
Key Takeaways:

• Apex cursors allow for scalable data processing of up to 50 million rows with enhanced control, including dynamic chunk sizing and the ability to pause and resume transactions.

• Batch Apex demonstrated superior performance in scenarios with light processing loads, while Apex cursors outperformed in scenarios requiring state preservation and fewer transactions, particularly in heavy processing workloads.

• Developers are encouraged to migrate jobs to Apex cursors when greater control or stateful processing is needed, while simpler jobs with fewer records can often be managed with lightweight solutions like Queueable Apex.

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