Best practices for Reltio Data Sharing with Databricks with Streaming tables
Learn more about best practices for using Reltio Data Sharing with Databricks so that you can choose the recommended compute type, query the supported tables and views, and avoid unsupported downstream usage.
Recommended practices
Use data shares for analytics and data engineering workloads
Use data shares for downstream systems such as BI, reporting, and ML pipelines.
Query supported streaming tables
Use the following streaming tables to query data.
entity_<entity_type>relation_<relation_type>-
interaction_<interaction_type> activitieslinksmatchesmergesworkflows
Based on the data share setup, these streaming tables use a simplified schema, which makes the data easier to consume in downstream applications.
Note: The data share supports a cumulative maximum of 490 entity, relationship, and interaction types. If your business configuration defines more than 490 of these types, apply filtering to limit the data share to 490 types. Contact Reltio Support to learn more about configuring the filter.
Practices to avoid
Avoid querying landing tables
Do not use the following streaming tables to query data.
entities_<entity_type>_landingtablerelations_<relation_type>_landingtableinteractions_<interaction_type>_landingtablelinks_landingtablematches_landingtablemerges_landingtableworkflows_landingtable
Avoid using data shares for non-analytics downstream systems
Do not use data shares to build downstream systems for non-analytics use cases.