Last updated: March 18, 2024
Supported data sources
The list of data sources supported by DQOps for running data quality checks, and measuring the data quality.
Overview
DQOps supports integration with different types of data sources for monitoring the data quality. To monitor data quality in DQOps, you must first add a data source connection. A data source connection specifies the parameters needed to connect to a database, such as a database location and authentication information. The data source connection information for each data source type may be different. Some data sources use existing database connection APIs (such as JDBC drivers), and others have proprietary APIs.
In DQOps, you can add a new data source connection through the user interface, command line or DQOps shell. For information on the parameters you need to specify, see the document dedicated to each data source.
Supported data sources
DQOps supports the following data sources.
AlloyDB for PostgreSQL
Amazon Athena
Amazon Aurora
Amazon Redshift
Amazon RDS for MySQL
Amazon RDS for PostgreSQL
Amazon RDS for SQL Server
Azure Database for MySQL
Azure Database for PostgreSQL
Azure SQL Database
Azure SQL Managed Instance
Azure Synapse Analytics
Google BigQuery
Cloud SQL for MySQL
Cloud SQL for PostgreSQL
Cloud SQL for SQL Server
CockroachDB
CSV
Databricks
DuckDB
JSON
MariaDB
Microsoft SQL Server
MySQL
Oracle
Percona Server for MySQL
Parquet
PostgreSQL
Presto
SingleStoreDB
Snowflake
Spark
Trino
YugabyteDB
What's more
- Learn how to configure connections to data sources in YAML files.