These are synchronous APIs that are used to perform create, update or upsert operations for up to 100 records in a Zoho CRM module. While the Insert Records API and Update Records API is used to create and update a record respectively, the  Upsert Records API is used to upsert (insert or update) a record depending on the availability of the record in your org . In Upsert Records API, the system checks for duplicate records based on the values in the duplicate_check_fields json array in the input json. If the record is already present, it gets updated. If not, the record is inserted. You will get the status of these operations immediately. Read more about the Upsert Records API in this Kaizen post.

Clearly, if you have more than 5000 records, it is advisable to use the bulk write API, given that you are ok with the operation being run asynchronously. If you want instant results, you should use insert/update/upsert APIs. However, more API credits will be consumed in this case.

Consider an e-commerce company where the Order management team uses a legacy system and the Accounts team uses Zoho CRM. To ensure that the Accounts team works with near real-time data in Zoho CRM, data synchronization from the legacy application is essential. Assume that in Zoho CRM, there is a custom module named "Orders" that contains the details from the legacy system. Imagine that you are in charge of the data synchronization between Zoho CRM and the legacy system. How should you call these APIs to achieve this synchronization? The synchronization process involves two steps. 

1) Unique field in Order Module: Maintain a unique field "parent_id" in the "Orders"  module. The unique identifier of the orders in your legacy system should be mapped to this parent_id field. In create bulk write job, this can be achieved by the section field_mappings. For ensuring correct working of upsert operations, you can make use of "find_by" field inside resource JSON Array in the Create Bulk Write Job API Request.  You should provide the value of "find_by" as the unique field "parent_id" .  To read more about find_by field refer to Create Bulk Write Job page.

2) Sync Flag in the Orders table in legacy system: For the sync, maintain a flag in your legacy system orders table for indicating whether the record is synced with Zoho CRM or not. Once the sync is done, update the flag to  true. Whenever a record is modified or sync fails, the flag value should be updated to false. This ensures that in case a record that is synced gets updated during the initial sync process, this flag column helps us re-sync this record again.

3) Grouping of data to batches:  For initial sync, the data volume in the table will be huge. So they have to be batched in a group of 25k records. This grouping can be done based on sorting the table with a particular column & filtering records based on the sync column with criteria sync=false.

Instead of making API calls to Zoho CRM on every data operation, store the data in a temporary data store like a DB table or Redis. Once 100 records are accumulated in that data-store, the Upsert Records API can be promptly invoked with all these record details and followed by emptying of the data store. This approach will lead to lower consumption of API credits.

There are chances that in a period of 10 mins, 100 record operations may not happen. Scheduler jobs or CRON jobs can be created to handle the records in the data store to update records to Zoho CRM. Once these records are handled, the data store should be emptied.