Parquet File to Sisense Integration
AI-first ETL from Parquet File into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Parquet File into Sisense
Datrise syncs Parquet File's row groups, columns, schemas, partitions, file batches, and column statistics into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.
Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.
Ideal for embedded analytics on an in-memory engine.
Endpoints
Parquet File: Columnar Parquet files from lakes and exports.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Parquet File entities map to Sisense
| Parquet File entity | Sisense object | Notes |
|---|---|---|
| row groups | parquet_file_row_groups | id PK · custom fields → flattened columns for the cube |
| columns | parquet_file_columns | id PK · linked to parquet_file_row_groups |
| schemas | parquet_file_schemas | id PK · linked to parquet_file_row_groups |
| partitions | parquet_file_partitions | id PK · linked to parquet_file_row_groups |
FAQ
How does Datrise handle Parquet File's custom fields in Sisense?
Flexible values are stored as flattened columns for the cube, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Sisense types.
How does the Parquet File to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
Related pipelines
More destinations for Parquet File
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