How to Reduce Database Sprawl: Strategies for Efficient Data Governance
Database sprawl is a significant issue for many organizations, characterized by the proliferation of specialized databases. This can lead to inefficiencies, increased costs, and heightened risks. As we explore the causes and solutions for database sprawl, we also provide actionable strategies to help reduce its impact.
Understanding Database Sprawl
Database sprawl refers to the phenomenon where an organization finds itself using a diverse array of specialized databases to manage different aspects of its data. Initially, this may not seem problematic. However, as more specialized databases are introduced, the complexity grows. When these databases need to communicate with each other, it can become a costly and risky endeavor.
The underlying issues arise from technological advancements and changing business requirements. For example, the proliferation of NoSQL databases and other specialized solutions during the early 2000s addressed the scalability and flexibility needs of internet applications. However, this led to a situation where various departments may have adopted different tools, leading to a fragmented database landscape.
Causes of Database Sprawl
Several key factors contribute to the growth of database sprawl:
Explosion of Specialized Database Companies: The early 2000s saw a surge in specialized database companies, each offering specific features and capabilities. This led to a "best-of-breed" approach where different tools were chosen based on specific needs. Lack of Governance: The ease with which developers can spin up new databases without proper governance can exacerbate the problem. Many database vendors offer free or freemium services, making it tempting for developers to use multiple tools. Expanding Application Scale: The rise of internet applications necessitated more scalable and flexible database solutions, leading to the adoption of NoSQL databases and other specialized technologies.Strategies to Reduce Database Sprawl
To effectively manage database sprawl, organizations need to adopt a strategic approach. Here are several key strategies:
1. Develop a Standard
One of the most effective ways to reduce database sprawl is to establish a standard database that addresses a broad range of needs. While selecting a standard may seem daunting, it's essential for businesses to at least stop making the problem worse. This involves educating developers and ensuring they use a consistent standard from the beginning of application development.
2. Consolidate Where Possible
Consolidation is a more complex task, but it is crucial to consider. Organizations should take a hard look at re-platforming to the standard database whenever a change is made, such as during a hardware refresh for on-premises databases or an application rewrite for cloud databases. While re-platforming can be expensive and time-consuming, it is a worthwhile investment over time. The consolidation process will gradually reduce sprawl and bring about cost savings.
3. Choose a Standard Database with Consolidated Capabilities
Look for a database that can handle a wide range of capabilities. Hybrid Transactional/Analytical Processing (HTAP) databases are particularly useful in this regard. HTAP databases combine transactional and analytical processing in a single engine, reducing the need for multiple specialized databases. As an example, I recently started working on a HTAP database that I am impressed by, and I believe it can significantly streamline data management.
Conclusion
Database sprawl poses a real challenge for businesses, leading to increased costs, time wasted, and heightened risks. However, with a well-thought-out strategy, organizations can effectively manage and reduce this issue. By adopting a standard database and focusing on consolidation, businesses can achieve a more efficient and cohesive data management approach. The goal is to maintain a balance between specialized needs and overall efficiency, ensuring that the chosen tools meet the organization's evolving needs while minimizing complexity and costs.
Key Takeaways:
Understand the root causes of database sprawl, including the proliferation of specialized databases and the lack of governance. Develop a standard database to streamline data management and reduce fragmentation. Consolidate where possible to minimize the number of databases and reduce costs. Consider HTAP databases for their flexibility and comprehensive capabilities.By implementing these strategies, businesses can effectively reduce database sprawl and enhance their overall data management capabilities.