Glassfrog to Amazon Athena Integration

How Datrise loads Glassfrog into Amazon Athena

Datrise syncs Glassfrog's circles, roles, people, accountabilities, projects, and governance records 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

Glassfrog: Holacracy roles, circles, and governance records.

Amazon Athena: Serverless SQL over S3 data lake tables.

How Glassfrog entities map to Amazon Athena

Glassfrog entity	Amazon Athena object	Notes
circles	`glassfrog_circles`	id PK · custom fields → struct/map columns in Parquet
roles	`glassfrog_roles`	id PK · linked to glassfrog_circles
people	`glassfrog_people`	id PK · linked to glassfrog_circles
accountabilities	`glassfrog_accountabilities`	id PK · linked to glassfrog_circles

FAQ

How does Datrise handle Glassfrog'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 Glassfrog 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.

Related pipelines

Early access

Connect Glassfrog to Amazon Athena the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.