Use cases

1. Microservice database consolidation

Consolidation

In a microservices architecture, each service has its own database. This poses a number of problems for reporting:

  • Performing reporting queries on a production database will slow it down and make access times unpredictable.
  • Indexes required for reporting add an overhead on the insert/update/delete operations.
  • It is not possible to query across multiple databases.

kuvasz-streamer consolidates all the databases of all services into a single data warehouse. Only the required tables and columns are replicated.

The schema in the data warehouse does not have to follow the same one as the original services.

2. Multi-tenant database consolidation

multinenant

In a sensitive multi-tenant environment, each tenant is assigned a separate database to ensure that no cross-pollination of data occurs. However, all the tenant databases have the exact same schema.

This poses a problem for cross-tenant reporting and customer support. kuvasz-streamer can be used to consolidate all the data in a single database. A newly added column sid identifies the source tenant database.

3. Database performance optimization

optimize In a high-performance system, historical data is kept to a minimum in order to provide quick query time and low latency to end users. A cleaner process usually deletes all data older than a certain number of weeks. If tables are partitioned, old paritions are dropped.

However, historical data is important for, AI/ML, reporting and forensics. kuvasz-streamer can be configured to ignore the DELETE and TRUNCATE operations on some tables and only apply the INSERT and UPDATE operations. A separate cleaner running on the data warehouse database takes care of removing older historical data.

Example usage includes transaction tables and audit history tables.

4. Postgres major version upgrade

upgrade Upgrading major versions of Postgres is a time-consuming task that requires substantial downtime. kuvasz-streamer can be used to synchronize databases between different versions of Postgres and then performing a quick switchover.