| KB ID: | 4878 |
| Product: | Veeam Data Cloud for Salesforce |
| Published: | 2026-07-07 |
| Last Modified: | 2026-07-07 |
This article explains the Data Import feature in Veeam Data Cloud for Salesforce (VDCSF): what it does, which sources it currently supports, and how to prepare data for importation.
This article is a feature summary only. Full procedural documentation can be found in the VDCSF User Guide.
The Data Import feature brings backup data that a customer already holds into VDCSF, preserving their backup history when migrating from another solution. The data can come from a supported third-party Salesforce backup tool or from exports of on-premises Veeam Backup for Salesforce (VBSF).
The exported CSV files are uploaded to cloud storage, and a Data Import job is then run. The job merges the data into the customer's VDCSF backup, creating a restore point for each imported snapshot. Once the import finishes, standard VDCSF restore works on the imported points, and regularly scheduled backups continue incrementally from there, without re-downloading data or creating duplicate records.
Like an initial full backup, a Data Import job can take anywhere from a few hours to several days, depending on the volume of data being imported. Customers should plan their cutover from the legacy solution accordingly.
Data Import supports object record data in CSV format from the following two sources:
Note: Files and Attachments, Salesforce configuration metadata, Big Objects, and Events are not supported.
The exported CSV files must be uploaded to Amazon S3 or Azure Blob Storage. Veeam Data Cloud for Salesforce connects to that location to read the files; it never writes to it.
.gz), or in a password-protected ZIP archive (.zip). The password is entered when the import job is started and is not stored afterward.Each file name must identify the object and follow this pattern:
ObjectName[__h][-NNN].csv[.gz|.zip]
Account.csvAccount__h.csvAccount-001.csv.gz, Account-002.csv.gz- or _) must appear before the digits so they are read as part of the split and not the object name.Any file that doesn't match this pattern will cause the whole job to fail before anything is imported, so file names should be verified before uploading.
day_YYYYMMDD_HHMMSS (an optional suffix, e.g. -abc123, is allowed). Seconds precision is required, and every folder in the job must have a unique timestamp. Files placed outside a day_* folder (including the storage root) are not supported and will cause the import to fail.Note: Own and VBSF exports cannot be imported in the same job. A single import job must use only one export format, even across different objects, so each export type requires its own job.
Id column, plus IsDeleted and the incremental-tracking field where those exist for the object. If a required column is missing from even one folder, the whole object fails to import (no partial import).The Data Import job reports one of four statuses when it finishes:
| Status | Meaning |
| Success | All objects/folders were imported with no issues. |
| Warning | Import completed, but some data was skipped (see below) or part of a multi-object job failed while the rest succeeded. |
| Failed | The job did not import any data. The job log identifies the reason, and the source data must be corrected before retrying. |
| Skipped | No matching files were found in the storage location (or a file filter excluded everything). |
If a job fails or only partially completes, there is no need to start over. The whole job, a single file, or a filtered subset of files can be re-run, and VDCSF will pick up where it left off without creating duplicate records or gaps in restore-point history.
To limit a (re)run to a subset of files, the File Name Pattern option can be used. It accepts a regular expression matched against the file/folder path. For example:
day_2026031[9]|day_2026032AccountThe pattern is case-sensitive and is applied on every retry, which is important to consider when importing the remaining folders or objects later.
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