Integrations
It integrates with what you already have.
A data platform is built in layers. Here you see which ones there are, which technologies fit each one and how they connect to your stack, without forcing you to switch vendors.
The layers
From ingestion to consumption.
Each layer can be chosen and changed on its own. Tap one to see what it does and when it makes sense.
01
Sources & ingestion
- What it does
- Where the data comes in from.
- When it makes sense
- When data lives in different systems and has to be brought together without touching the originals.
- Common technologies
- Tap a technology to learn more.
Planner
Plan your integration.
Choose where your data comes from, what you need and where you want it. We show a possible path and then fine-tune it together.
A possible path
- 1
Ingestion
Change data capture (CDC) with Debezium into Kafka, without loading your operational database.
- 2
Orchestration
Airflow, Dagster, or Azure Data Factory, with schedules, retries and alerts.
- 3
Platform
Snowflake as warehouse and query engine.
- 4
Modeling
dbt to model the data and test it.
- 5
Governance
Role-based permissions, lineage and data quality from day one.
- 6
Consumption
Dashboards in Superset, Power BI or Looker on the same tables.
Indicative only. The final architecture depends on your volume, your permissions and your team.
Tell us and we will fine-tune it →