Database Object Management Automation

Zdravko Yanakiev
December 18, 2023
Read: 4 min

Database object management automation is the use of automated processes and tools to handle various aspects of managing database objects within a database system.

This approach is favoured over manual methods because it reduces the risk of human error, ensures consistency across environments, maintains version control and enables scalability.

Furthermore, by reducing manual effort and providing a standardised approach, database object management automation helps you improve reliability, streamline operations and enable collaboration within complex database environments.

The problem with manual database object management

Database objects include entities such as schemas, tables, views, stored procedures, user-defined functions, and more.

In small-scale scenarios, these are created, configured and deleted by database operators and developers using ad-hoc SQL queries or throwaway scripts. However, this becomes increasingly impractical and error-prone as the complexity of the database environment grows.

Business advantages of automated database object management

Database object management automation offers numerous technical benefits, translating into tangible business advantages as detailed below.

Improved operational efficiency and risk mitigation

By reducing the occurrence of errors and ensuring a consistent approach, the risk of operational disruptions is minimised, productivity is enhanced, and business operation becomes more reliable and efficient.

Accelerated time-to-market and resource optimisation

Automation not only reduces the time routine tasks require but also allows for the swift deployment of new database instances. This accelerates the time-to-market for applications and updates, which provides a strong competitive edge.
Additionally, automation saves development time, so your engineers can focus on higher-value tasks.

Enhanced collaboration and knowledge management

Version control and standardised automation processes foster enhanced collaboration among team members. This also promotes knowledge sharing and best practices.
When the team is well-informed and collaborates successfully, productivity is higher and there is a more cohesive working environment.

Risk mitigation and regulatory compliance

Automation creates fully transparent, traceable records that support auditing and compliance efforts. This brings a twofold benefit. First, it significantly mitigates the risk of legal and reputational issues. Second, it builds confidence among stakeholders regarding data security and compliance with regulatory requirements.

Scalability and cost-efficiency

The modular structure of database object management automation facilitates scalability and contributes to cost efficiency at the same time.
Organisations can adapt to changes and expansions without significant resource investments, optimising costs and ensuring a scalable and adaptable infrastructure. Additionally, the reuse of proven components reduces the effort required for new automation scripts, ensuring the most efficient use of resources.

Tech benefits of database object management automation

Efficiency, consistency and fewer errors

Some of its primary advantages are increased efficiency and consistency. Automated processes ensure that database objects are created, modified and deleted standardised and error-free, minimising the risk of human error and promoting consistency across different environments.

This not only enhances the overall efficiency of database management but also reduces the likelihood of discrepancies that can arise from manual interventions.

Saving time

The time-saving aspect of automation is significant, as routine tasks such as schema modifications and configuration changes can be executed more quickly and consistently.

Reusable templates for different object types reduce the time it takes to deploy new object instances to the database environment. Automated solutions free up valuable time for developers, which allows them to focus on more strategic aspects of database management and application development.

Version control and collaboration

Version control is another critical benefit, as version control systems track and manage changes to database object management code systematically.

Collaborative efforts are further streamlined as automation provides a standardised and easily reproducible approach. As a result, the chance of misunderstandings and discrepancies among team members is dramatically reduced.

Pull request reviews in version control platforms further increase the code quality and reduce the risk of bugs being introduced into production environments.

Auditing and compliance

For auditing and compliance purposes, database object management automation ensures a transparent and traceable record of all changes that have been made to the database schema and objects.

This audit trail is crucial for regulatory compliance, security assessments and internal governance. Automation tools help organisations maintain a clear picture of who made changes, when and what those changes entail. You get a secure and fully compliant database environment.

Modularisation and reusability

By structuring automation scripts into modular components, each designed to handle specific database tasks or objects, the code becomes more versatile and adaptable. This modular approach allows for easier maintenance, updates, and troubleshooting as changes can be made to individual modules without affecting the entire automation system.

Furthermore, reusing code modules across different projects or environments promotes consistency and efficiency. Teams can leverage proven and tested components, reducing the effort required to create new automation scripts. Standard modules can also be written to facilitate the creation of role hierarchies fulfilling (Personally Identifiable Information) PII protection requirements.

Implementation guide

While the practical implementation of database object management automation will inevitably vary with different database setups, requirements and technologies it typically involves the following aspects.

  1. Choosing a tool
    Choose an automation tool aligning with your organisation's needs, tech stack, preferred languages and database used.
    At Infinite Lambda, we often work with the Snowflake Data Cloud because of its strong flexibility and scalability advantages. Here two excellent tools for managing Snowflake environments:

    • SnowDDL – a declarative tool for object management automation in Snowflake
    • Snowflake Terraform – a Terraform provider for managing Snowflake resources
  2. Implementing Version Control
    Establish a version control repository, leveraging VCS like Git and collaboration platforms like GitLab or GitHub. This enables change tracking, collaboration and code reviews.
  3. CI/CD Integration
    Implement CI/CD pipelines for automated testing and deployment. These typically test object management code, provide a preview of actions to be executed and apply them to the database environment.
  4. Documentation
    Comprehensive documentation is crucial for knowledge transferability. Include comments in the code and write runbooks outlining development and deployment steps. This documentation aids troubleshooting and facilitates future developments.
  5. Testing
    Implement tests to validate the reliability and functionality of automation scripts. This guarantees that changes do not compromise existing functionalities. You can also include tests to validate the state of the database after applying automated changes.

Start automating

Manual database object management leads to an increased risk of errors, inconsistency across environments, and inefficiency in managing and modifying database objects. Automating this process provides business benefits by lowering costs, accelerating time-to-market, and enhancing scalability.


Infinite Lambda is a data and cloud consultancy and academy. We enable modern organisations like yours to adopt cutting-edge technologies and practices by strategising, implementing and providing guidance to set you up for success in the long run.

Get in touch with us to tell us about your goal and challenges with the modern data stack.

More on the topic

Everything we know, we are happy to share. Head to the blog to see how we leverage the tech.

Tag-Based Masking in Snowflake
Tag-Based Masking in Snowflake: Practical Guide with Scalable Implementation
As data continues to be a critical asset for organisations across industries, safeguarding sensitive information while enabling data access for authorised users is a constant...
June 11, 2024
Cloud sustainability
Cloud Sustainability
This article on cloud sustainability is a part of a series on carbon analytics published on the Infinite Lambda Blog. Appreciating the cloud is becoming...
June 5, 2024
How to measure happiness and safety in tech teams
How to Measure Happiness and Safety in Tech Teams
Software product development initiatives can go awry for a whole range of reasons. However, the main ones tend not to be technical at all. Rather,...
May 30, 2024
why sustainability analytics
Why Sustainability Analytics
We all like a sunny day. Kicking back in the garden with the shades on, cool drink in hand and hopefully a liberal amount of...
May 8, 2024
Data diff validation in a blue green deployment: how to guide
Data Diff Validation in Blue-Green Deployments
During a blue-green deployment, there are discrepancies between environments that we need to address to ensure data integrity. This calls for an effective data diff...
January 31, 2024
GDPR & Data Governance in Tech
GDPR & Data Governance in Tech
The increasing focus on data protection and privacy in the digital age is a response to the rapid advancements in technology and the widespread collection,...
January 18, 2024

Everything we know, we are happy to share. Head to the blog to see how we leverage the tech.