If your Salesforce org is feeling sluggish after years of collecting data, it might be time to rethink how that data is stored. Big Objects could be the answer. They are built to handle huge volumes of information and keep your system performing well, even as your records continue to grow. However, they are not like standard or custom objects. Big Objects require thoughtful planning to make sure they stay efficient and cost-effective.
This guide covers everything you need to know. You will learn what Big Objects are, when they make sense to use, and simple design patterns that actually work. You will not need a background in data engineering to get started, just a clear approach and a few best practices that can go a long way.
What Are Big Objects?
Big Objects are Salesforce’s answer for storing truly massive datasets. They can hold billions of rows inside your org while keeping storage fees manageable.
Here are common ways teams use them:
- Archiving: Move closed cases, tasks, or other dormant records out of your main tables to reclaim space.
- Historical analysis: Capture daily or monthly snapshots so you can track long-term trends without bloating standard objects.
- Logging: Collect huge streams of integration events or system logs that would overwhelm normal storage.
How Big Objects Differ from Familiar Objects
- They sit on a dedicated, high-capacity storage layer that is separate from the data you work with every day.
- You must define a primary index before loading data, which keeps queries fast at scale.
- They do not support regular edits or Apex triggers. To read or load data, you use Async SOQL for queries or the Bulk API for inserts.
Design them well up front, and Big Objects become a powerful safety valve, letting your core data model stay lean while you keep every record you might ever need for reporting or compliance.
When Do Big Objects Make Sense?
Big Objects are not meant for everyday use cases, as they shine in specific scenarios. Below are some examples of when they are the right fit, and when to consider alternatives:
Best Scenarios
- You need to retain large volumes of data for compliance or audit purposes.
- The records are rarely modified and are mainly read-only.
- You need to lower the amount of costly standard object storage.
Situations to Avoid
- Your solution depends on live updates or frequent edits.
- You want highly detailed analytics with instant drill-down.
- You intend to display the data on Lightning pages just like regular records, because the user interface options are limited.
Best Practices for Working With Big Objects
Working with Big Objects is different from standard data handling in Salesforce. Here are key practices to help you maximize performance and avoid common pitfalls:
Plan the Index First
Your index decides how every query will perform, and you cannot change it once the object is live. Pick only the fields you will filter or sort, such as AccountId together with CreatedDate. Keep the index compact by skipping large text columns or anything you do not truly need.
Keep the Schema Lean
Store just the key details. Treat a Big Object as a smart archive rather than a replica of the original table.
Load Data in Batches
Use the Bulk API or batch Apex for high-volume loads. Constant single-record inserts consume resources and slow throughput.
Query with Async SOQL
Results arrive asynchronously, so build patience into your process. Always filter on indexed fields because full table scans are not practical at scale.
Combine With External Tools
For deeper analytics, push Big Object data to a data lake or business intelligence platform and leave only an active subset inside core Salesforce.
Follow these guidelines and your Big Objects will stay fast, efficient, and budget-friendly even as your data grows into the billions.
Proven Design Patterns for Big Objects
Below are four battle-tested patterns that help Salesforce teams store vast amounts of data without slowing down their daily work.
Archive Pattern
When to use: Move inactive records to free space and keep core objects slim.
How to build it:
- Keep only essential fields such as RecordId, ClosedDate, and Status.
- Create an index on RecordId and ClosedDate.
- Schedule a batch job to migrate aging records and remove them from the primary tables.
Event log pattern
When to use: Capture large streams of logs like API calls or user clicks.
How to build it:
- Core fields include UserId, EventType, EventDateTime, and Payload.
- Index on UserId and EventDateTime so you can filter by user or date range.
- Insert data with Bulk API or a chunked Apex loader.
Historical Snapshot Pattern
When to use: Track how a record looked at different points in time.
How to build it:
- Store RecordId, SnapshotDate, and the values you want to monitor.
- Index on RecordId and SnapshotDate.
- Run a daily or weekly job that copies the current state into the snapshot table.
Staging pattern
When to use: Land raw external data before transformation.
How to build it:
- Keep raw columns together with ExternalId and CreatedDate.
- Index on ExternalId and CreatedDate.
- Batch-process the data, cleanse it, then upsert it into standard objects.
- Purge the staging table on a regular schedule to control storage use.
Extra Tips to Keep Big Objects Healthy
To keep your Big Objects setup maintainable over time, keep these three habits in mind:
Start small by loading a representative sample to test performance before bringing in millions of rows. Document everything – from index fields, data model, retention rules, and any automation you set up. Future you will thank present you. And lastly, purge regularly, since Big Objects can grow without limit. Schedule a routine cleanup to remove data you no longer need and keep storage costs predictable.
Summary
Big Objects give your Salesforce org room to breathe by moving huge volumes of rarely edited data out of expensive primary storage and into a layer built for scale. That extra capacity means you can keep every case, log entry, or historical snapshot you need for audits, analytics, or regulatory compliance without watching performance slow to a crawl. Teams that adopt Big Objects often find day-to-day tasks feel lighter because reports, searches, and automation no longer sift through millions of older records.
To unlock that benefit, you must design with care. Start by defining a concise index that matches the way you will filter or sort, keep the schema trimmed to only essential fields, and load data in large batches through the Bulk API or batch Apex. Query with Async SOQL on indexed columns, document every choice you make, and schedule regular purges for information that is past its useful life. Follow these practices and your Big Objects will stay fast, predictable, and easy to maintain even as they grow into the billions.
