DatriseAI-first ETL

Lokalise to Amazon DynamoDB Integration

AI-first ETL from Lokalise into Amazon DynamoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Lokalise into Amazon DynamoDB

Datrise syncs Lokalise's projects, keys, translations, languages, contributors, and translation statuses into Amazon DynamoDB as an item per source record in a table per entity. Flexible or custom fields land in nested map/list attributes, and timestamps such as created, updated, and status changes are typed as ISO-8601 string or epoch number attributes.

Sync is incremental: Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id, so re-runs update only what changed. Partition-key design on the entity id to spread throughput evenly. DynamoDB rewards access-pattern-first key design, so Datrise sets partition/sort keys from your entity ids rather than scan-heavy defaults.

Ideal for serverless apps needing single-digit-millisecond key lookups on CRM data.

Endpoints

Lokalise: Translation management for product strings.

Amazon DynamoDB: Serverless key-value and document store on AWS.

How Lokalise entities map to Amazon DynamoDB

Lokalise entityAmazon DynamoDB objectNotes
projectslokalise_projectsid PK · custom fields → nested map/list attributes
keyslokalise_keysid PK · linked to lokalise_projects
translationslokalise_translationsid PK · linked to lokalise_projects
languageslokalise_languagesid PK · linked to lokalise_projects

FAQ

How does Datrise handle Lokalise's custom fields in Amazon DynamoDB?

Flexible values are stored as nested map/list attributes, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon DynamoDB types.

How does the Lokalise to Amazon DynamoDB sync stay up to date?

It runs incrementally — Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id.

Related pipelines

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