How to archive data in big object Salesforce?

Data in big object Salesforce: In the realm of Salesforce, efficient data management is critical for optimal performance and scalability. Salesforce Big Objects offer a robust solution for handling vast amounts of data. In this guide, we’ll explore the intricacies of archiving data in Salesforce Big Objects, providing a step-by-step walkthrough, best practices, and valuable insights to streamline your data management strategy.

How can I effectively archive data in Salesforce using Big Objects?

Achieve efficient data archiving in Salesforce by leveraging Big Objects. Follow our comprehensive guide, covering step-by-step instructions, best practices, and FAQs. Streamline your data management and optimize performance with confidence.

Understanding Salesforce Big Objects:

Salesforce Big Objects are a specialized type of object designed for handling and storing large volumes of data efficiently. They are particularly useful for archiving historical records, keeping the core Salesforce database agile and responsive.

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How to Archive Data in Salesforce Big Objects:

Step 1: Evaluate Archiving Needs

Determine which records and data subsets are suitable for archiving. This involves analyzing historical data that is no longer frequently accessed but needs to be retained for compliance or reporting purposes.

Step 2: Create a Big Object

  1. Log in to your Salesforce environment.
  2. Navigate to Setup and enter “Big Objects” in the Quick Find box.
  3. Select “Big Objects” and click “New Big Object.”
  4. Define the object’s properties, such as the name and storage size.
  5. Save and deploy the new Big Object.

Step 3: Design a Data Archiving Strategy

Develop a comprehensive strategy for moving and managing data in your Big Object. Consider factors like data relationships, indexing, and query patterns to ensure optimal performance.

Step 4: Extract and Transform Data

Use Salesforce Data Loader or other ETL (Extract, Transform, Load) tools to extract data from standard objects and transform it into the format suitable for the Big Object schema. Pay attention to data mappings and relationships during this process.

Step 5: Load Data into Big Objects

Once your data is transformed, load it into the Big Objects using the appropriate Salesforce tools. This process may involve bulk data load jobs or other data migration tools.

Step 6: Implement Archiving Logic

Create triggers or processes to identify records eligible for archiving and automate the data transfer from standard objects to Big Objects. Establish clear criteria for when data should be archived to maintain accuracy and relevance.

Step 7: Optimize Query Performance

Leverage features like indexing and query optimization to ensure efficient data retrieval from Big Objects. Understand the query patterns of your application and adjust indexing accordingly.

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Best practices of archive data in big object Salesforce

Archiving data in Salesforce using Big Objects involves a set of best practices to ensure a smooth and effective process. Here are key recommendations:

  1. Data Analysis and Segmentation:
    • Conduct a comprehensive analysis to identify data suitable for archiving. Segment data based on factors such as age, relevance, and compliance requirements.
  2. Archiving Policy Definition:
    • Establish a clear archiving policy outlining criteria for moving records to Big Objects. Define rules for archiving based on business needs, compliance regulations, and data access patterns.
  3. Optimal Schema Design:
    • Carefully design the schema for your Big Objects. Consider relationships, indexing, and the specific archiving requirements to ensure an efficient and scalable data structure.
  4. Data Transformation and ETL:
    • Use ETL tools to extract and transform data from standard objects before loading it into Big Objects. Ensure accurate mapping and handle any data relationships appropriately during this process.
  5. Bulk Data Loading:
    • Leverage Salesforce Data Loader or similar tools for efficient bulk loading of data into Big Objects. Monitor and optimize the loading process to maintain performance and minimize impact on other operations.
  6. Automation Logic Implementation:
    • Implement automation logic, such as triggers or processes, to identify and move eligible records from standard objects to Big Objects. Clearly define the criteria for when data should be archived.
  7. Query Optimization:
    • Optimize queries for efficient data retrieval from Big Objects. Utilize indexing and understand the query patterns of your application to enhance performance during data retrieval.
  8. Regular Monitoring and Maintenance:
    • Establish a routine for monitoring the archiving process. Regularly review and adjust archiving criteria based on changing business needs. Perform maintenance tasks, including purging unnecessary data.
  9. Documentation and Communication:
    • Document the archiving strategy, schema design, and any automation rules implemented. Communicate changes to relevant stakeholders and provide training to users on the updated data management processes.
  10. Compliance Checks:
    • Ensure that your archiving strategy aligns with data privacy regulations and compliance requirements. Regularly review and update archiving practices to stay in compliance with evolving standards.
  11. Testing and Validation:
    • Thoroughly test the archiving process in a sandbox environment before implementing it in production. Validate data accuracy, system performance, and the effectiveness of the archiving strategy.

FAQs and External Resources:

Frequently Asked Questions (FAQs):

Q1: Can I archive data from any Salesforce object to Big Objects?

  • While many standard and custom objects can be archived, not all are suitable. Refer to Salesforce documentation for object compatibility.

Q2: Are there storage limits for Big Objects?

  • Yes, each Salesforce edition has specific storage limits for Big Objects. Consult Salesforce’s official documentation for current limits.

Q3: How does archiving affect data relationships?

  • Archiving data to Big Objects maintains relationships, but queries may require adjustments. Ensure a thorough understanding of your data model.

External Links:

  1. Salesforce Big Objects Documentation
  2. Salesforce Data Management Guide


Data archiving in Salesforce Big Objects is a powerful strategy for maintaining a responsive and efficient Salesforce instance. By following this comprehensive guide, you’ve gained insights into the steps involved in archiving data, best practices, and answers to common questions. Continuously refer to Salesforce’s official documentation and leverage the wealth of resources available to refine your data management strategy and ensure optimal performance as your Salesforce instance scales.