Data Warehouse
Layering, naming, loading, transformation, and model-evolution conventions for a managed enterprise warehouse.
The Synthebase platform
Everything a Data Warehouse needs—from source connection to operations.
Synthebase is not a separate orchestrator or a collection of SQL scripts. It is a complete platform around PostgreSQL: a powerful ETL Engine, DWH and Data Lake architecture, modeling conventions, execution control, and tooling for the data team.
10+ yearsof Engine development and operation
Multiple organizationsreal enterprise use cases
One technology foundationPostgreSQL + SQL + FDW
More than ETL
The complete modern data platform.
Data Lake
External data, files, and Big Data through FDW and SQL—without breaking the workflow between lake and warehouse.
Built-in ETL Engine
Scheduling, dependencies, parallel execution, retries, recovery, monitoring, and full run history inside PostgreSQL.
The decisive advantage
No second platform between engineers and their data.
Synthebase uses PostgreSQL as the compute core, orchestrator, process catalog, and operational ledger. Teams work with one transactional model, one SQL language, and familiar tools—without a proprietary DSL or hidden metadata layer.
Sources become tables
FDW opens one SQL access layer across a vast range of systems and formats.
Transformations stay SQL
Code remains easy to read, verify, debug, and evolve with the team.
Execution stays visible
Status, history, errors, retries, and metrics are available where the data lives.
Open data ecosystem
Databases, Big Data, files, streams, and external REST APIs.
Synthebase connects relational and NoSQL systems through the broad FDW ecosystem. External REST APIs are called by PL/pgSQL procedures in the same Engine, giving API ingestion the same schedules, retries, execution history, and monitoring as every SQL pipeline.
Databases and cloud warehouses
PostgreSQL
Oracle
MySQL
SQL Server
IBM Db2
SQLite
MongoDB
Redis
Elasticsearch
BigQuery
Big Data, streams, and external APIs
Hadoop
Apache Hive
Parquet
Apache Kafka
REST / OpenAPI
JSON
Analytics and team operations
Apache Superset
Slack
Git
CLI
The complete data lifecycle
From ingestion to dashboards and self-service—without breaking the platform.
Apache Superset is integrated with the DWH at the database level and operates in the same PostgreSQL environment. Data marts, metadata, automation, and operational monitoring form one system while business users gain dashboards and independent data exploration.
01 · Sources
Databases, files, and REST APIs
FDWs, foreign tables, and PL/pgSQL calls to external APIs.
02 · Platform
ETL + DWH + Data Lake
SQL transformations, schedules, retries, history, and quality control.
03 · Analytics
Apache Superset
Data marts, dashboards, SQL Lab, and one self-service analytics layer.
04 · Operations
Keep the team informed
Monitoring, automation, and operational alerts delivered to Slack.
Operational feedback is built in.core.monitoring sends ETL delays and failures to Slack; the same integration layer can extend to webhooks, email, Teams, or PagerDuty.
Product family
From one PostgreSQL instance to a distributed enterprise platform.
Editions differ in operational scale and accountability while sharing the same Engine, SQL model, and DWH approach.
Core
PostgreSQL-native ETL/ELT for focused jobs, small warehouses, and a fast first deployment.
Platform
The complete toolkit for a data team: CLI, connectors, DWH conventions, monitoring, and repeatable delivery.
Enterprise
Distributed execution, governance, certified deployment, and accountable support for critical data estates.
Cloud
A dedicated Synthebase data platform operated for teams that want to focus on data, not infrastructure.
Editions
Choose the operating model that fits your team.
| Edition | Designed for | Deployment | Primary value |
|---|---|---|---|
| Core | Engineer or small team | One PostgreSQL | Fast PostgreSQL-native ETL/ELT |
| Platform | Data team | Self-managed | Complete DWH toolkit and team workflow |
| Enterprise | Large organization | On-prem / private cloud / BYOC | Distribution, governance, and support |
| Cloud | Teams of any scale | Managed dedicated platform | Data outcomes without operational load |