Source Datastore
Qualytics connects to Source Datastore using "Datastores," a framework that enables organizations to:
- Connect with Apache Spark-compatible source datastore.
- Support both traditional databases and modern object storage.
- Profile and monitor structured data across systems.
- Ensure secure and fast access to data.
- Scale data quality operations across platforms.
- Manage data quality centrally across all sources.
These source datastore integrations ensure comprehensive quality management across your entire data landscape, regardless of where your data resides.
Understanding Datastores
A Datastore in Qualytics represents any structured source datastore, such as:
- Relational databases (RDBMS)
- Raw files like CSV, XLSX, JSON, Avro, or Parquet
- Cloud storage platforms like AWS S3, Azure Blob Storage, or GCP Cloud Storage
Qualytics integrates with these source datastores through a layered architecture:
Available Datastores Connector
Qualytics supports a range of source datastores, including but not limited to:
| No. | Source Datastores |
|---|---|
| 1. | Athena |
| 2. | Databricks |
| 3. | DB2 |
| 4. | Hive |
| 5. | MariaDB |
| 6. | Microsoft SQL Server |
| 7. | MySQL |
| 8. | Oracle |
| 9. | PostgreSQL |
| 10. | Presto |
| 11. | Amazon Redshift |
| 12. | Snowflake |
| 13. | Synapse |
| 14. | Timescale DB |
| 15. | Trino |
| 16. | Dremio |
| 17. | Amazon S3 |
| 18. | Google Cloud Storage |
| 19. | Windows Azure Storage Blob |
| 20. | Azure Blob File System |