1С:CRM → Amazon Athena
AI-first ETL from 1С:CRM into Amazon Athena. Governed entities, incremental sync, typed landing tables.
How Datrise loads 1С:CRM into Amazon Athena
Datrise syncs 1С:CRM's contacts, accounts, deals, activities, and lifecycle events into Amazon Athena as partitioned Parquet in S3 exposed as an Athena table. Flexible or custom fields land in struct/map columns in Parquet, and timestamps such as created, updated, and status changes are typed as timestamp.
Sync is incremental: Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog, so re-runs update only what changed. Hive-style partitioning by load date so Athena scans only new data. Athena bills per byte scanned and small files hurt, so Datrise compacts to right-sized Parquet rather than many tiny objects.
Ideal for serverless SQL over an S3 lake without a running warehouse.
Endpoints
1С:CRM: CRM with strong adoption in CIS markets for sales and operations.
Amazon Athena: Serverless SQL over S3 data lake tables.
How 1С:CRM entities map to Amazon Athena
| 1С:CRM entity | Amazon Athena object | Notes |
|---|---|---|
| contacts | 1c_crm_contacts | id PK · custom fields → struct/map columns in Parquet |
| accounts | 1c_crm_accounts | id PK · linked to 1c_crm_contacts |
| deals | 1c_crm_deals | id PK · linked to 1c_crm_contacts |
| activities | 1c_crm_activities | timestamp events |
FAQ
How does Datrise handle 1С:CRM's custom fields in Amazon Athena?
Flexible values are stored as struct/map columns in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Athena types.
How does the 1С:CRM to Amazon Athena sync stay up to date?
It runs incrementally — Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog.
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