Mutate data safely
Dedicated insert, update, upsert, and delete operations apply schema validation and resource authorization. For a check-then-write flow, use a database transaction and keep remote network calls outside it. Bulk update and delete accept filters. Preview the affected selection in your application flow, then apply the mutation with a deliberately bounded scope. Schema validation, primary-key requirements, foreign references, and uniqueness can reject a write. Large filtered update/delete operations are executed in bounded batches; a later batch failure does not make a previously committed batch disappear unless the caller used an explicit transaction-capable runtime flow. Design idempotency and retry behavior around the operation you selected.Conditional upserts
Use conditional upserts when an integration sends repeated snapshots. They reduce redundant writes and row-audit updates while preserving the normal schema, permission and transaction checks. The options are available in low-code and the Platform API in the 3 November update to 1.7.1. For a Database withproductId, cost, currency, active and updatedAt columns:
filter checks the current Database row and controls updates only. A missing row is inserted independently of that filter. The example can update an existing active product; it does not reactivate an inactive product merely because the incoming value is true.
Use skipUnchanged: true to compare all supplied fields other than primary keys. An exclude list omits technical fields from that decision; an include list compares only the selected business fields. Choose one list, with known non-primary-key column names. When a compared field changes, all supplied PATCH fields are written together. Changes only to excluded fields are intentionally not saved.
Omitted fields remain unchanged, explicit nullable null clears a value, and non-nullable null retains the documented default-reset behavior. JSON compares stored text; JSONB compares structure. Existing calls keep their defaults, including returned row data and PATCH behavior.
In conditional mode, success counts handled input records, including intentional skips; affected counts actual writes. Returned data contains written rows only. Set return: false when row data is unnecessary to reduce response overhead. Skipped updates do not create row-audit changes. The conditional options apply only to upsert, not ordinary insert.
The filter uses the existing structured field/op/value syntax with and, or and not. It supports current target fields without joins, raw expressions or incoming-field references. See the low-code API reference for the complete option types.
Ordered mass updates
The Mass Update workspace accepts an ordered list of transformations. A column can appear more than once: for example, trim a text value and then append a suffix. Supported operations include assignment, arithmetic, boolean toggling, date changes, text editing, array membership changes and JSON transformations. Text editing covers insertion, literal replacement, trimming and case conversion. Arrays support adding or removing items; JSON supports merging, setting a path and removing a path. Transformations preserve NULL unless an explicit empty-value policy is selected. The API accepts at most 100 operations and validates the operands for each one. Preview the filtered selection before submitting. Ordered operations do not replace the normal authorization or transaction boundaries. See the current low-code API reference for exact operation shapes.Database exports
The export dialog offers CSV, TSV, NDJSON, and Excel (XLSX) for Tables and Views. Choose the destination, filename and access settings, then follow the asynchronous export through its job and resulting file. CSV remains the default when existing API or low-code callers omit the format. Excel preserves supported column types; values that exceed Excel’s numeric precision are written as text. The server checks the worksheet ceiling of 1,048,575 data rows plus a header and 16,384 columns during export execution. A REST request may already have been accepted when that check fails; low-code waits for the result by default. Exports are managed files in Storage. Export data to Storage explains all four formats, notification defaults, asynchronous receipts and finalized-file examples. See 1.5.0 for the related data and spreadsheet changes.Import from Storage
The import dialog accepts CSV, TSV, NDJSON, and XLSX. Choose insert or upsert mode and the row-error policy before selecting the file. The dialog reserves a Private Storage upload and registers the import operation before transferring bytes. Validation starts automatically after upload finalization; preview does not write rows. Hiding the dialog leaves the upload running in the application. Use Uploads to continue the import or View operation to inspect its progress. Closing or reloading the browser cannot resume an unfinished transfer; once the complete file has transferred, server-side validation continues independently. Review the validation report and proposed column mapping. Correct ambiguous mappings, wait for revalidation, and choose Commit to write. Commit checks that the source file and target definitions still match the preview. The Database operation routes also expose status, result, cancellation, and eligible failed-operation retry. Resource Write or Admin is required to start or change an import; Resource Read can inspect status. For files already in Storage, the Platform API preview accepts the existingstorageEntryId. The optional storageUploadSessionId registers validation while an upload is still in progress: the session must belong to the caller’s Private Storage and target that file. Repeating admission with the same upload and options reuses the operation. HTTP 202 confirms admission, not a completed import.
Import validation and commit phases produce in-app System messages. Review-required, success, and error messages can also send email according to notification preferences. Set skipNotification: true to suppress both channels; low-code imports suppress these messages by default.
Preserve exported values
CSV and TSV imports default to the escaped NULL convention used by Database exports:\N represents NULL, an empty string remains an empty string, and literal backslashes are escaped. This also applies after downloading and re-uploading an export without its original Storage metadata. For files from another system, select an explicit mapping.nullMode when their NULL convention differs.
An explicit nullable NULL remains NULL even when the column has a default. An omitted NDJSON property remains omitted, allowing insert defaults or a partial upsert. Large integers and precise decimals retain their supported text representation; XLSX DATE values must represent valid calendar dates.
Low-code uses api.importDatabase(), api.updateDatabaseImportMapping(), and api.commitDatabaseImport(); see Database API for the workflow and the generated API reference for signatures.
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