A Database Manager solution for customers, where objects (database, warehouse, users, roles etc) can be managed via a GitOps method. Currently, Snowflake and Google BigQuery is supported and we are working hard on Azure SQL support. Which consists of 4 steps which are explained further below: Lint -> Template -> Testing -> Deployment.
We deliver a container-based solution, which allows customers to generate and execute SQL for Snowflake or other via a template.
Benefits Acheron Database Manager
Benefits Acheron Database Manager
- Snowflake/Google BigQuery changes can be developed up to 40% faster using. Acheron’s template solution
- BI developers can roll out changes independently and fully automated
- Full traceability: every change is logged, both from BI developers and from the automatic rollout
- Code quality is guaranteed with the help of automatic tests, review process and templates
- Integrates with Enterprise secret managers (e.g. HashiCorp Vault)
Possibilities
- Git CI/CD
- Vault integratie
Lint stage
Fail-fast with the Linter’s automatic error recognizer. The Linter stage allows you to test the config files and template files against Acheron rules and your own rules, in order to detect errors at an early stage without any impact. And which allows you to easily debug and try again, until a reliable set is created to generate SQL code with. Which makes it possible to work with Standards.
Template stage
With the Acheron solution you can easily manage Database objects with templates, which enables you to generate complex SQL with simple configuration files. Which meets the standards that you have drawn up as a company.
Which makes it possible to generate and execute more SQL code than is possible manually, see below an overview of timelines between manual SQL scripting vs template developments
Testing Stage
The testing stage is optional to use and allows you to have the code executed first against a test environment instead of directly on your production environment. This is so that you can be sure that all code is 100% correct and can be executed on the environments.
If there are things that are not accepted, you will receive a clear colored logging return, in which the error is indicated. After correction, you can then go through the stages again to make the adjustments again to your environment.
Deployment stage
If the SQL code is successfully completed through all stages, it can be automatically executed on the environment. Think of the automatic roll-out of SQL code on, for example, your Database Test-Acceptance-Production environment.
If there are things that are not accepted, you will receive a clear colored logging return, in which the error is indicated. After correction, you can then go through the stages again to make the adjustments again to your environment.
Customer Experience Quotes
With less knowledge you can achieve more results
No more copying and pasting
Fewer mistakes because you literally see what Snowflake or Google BigQuery is doing
Roadmap
- Google BigQuery support
- SQL Support
- Secret manager Azure/AWS ondersteuning
Demo Acheron Database Manager
Project Info
- Category: Data solutions
- Client: Acheron
- Location: Nederland
- Completed Date: 2021