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TDWI Upside - Where Data Means Business

Keeping Up with the Latest Trends in the Database Market

These three key trends are likely to have a major impact on the market over the next year -- and beyond.

After decades of the status quo and incremental changes, the world of transactional databases is going through a period of rapid change. Data-driven organizations that are evaluating opportunities to innovate and set new business and technology priorities will benefit from a better understanding of the latest database trends that are shaping cloud-native application development. Staying on top of the most recent developments in the data layer ensures that organizations’ data strategy, technology investment, and resource allocations achieve the best business outcomes.

For Further Reading:

Apache Cassandra: Where Is the Open Source Database Headed? 

Cloud Database Trends and Reducing the Risk of Moving High-Stakes Workloads

Why Companies Are Turning to Database Virtualization Amid Market Uncertainty

These three key trends are likely to have a major impact on the market over the next year and beyond.

Trend #1: Shifting from monolithic databases to cloud-native distributed SQL

Organizations are modernizing their database footprint by migrating from traditional, monolithic database solutions (such as Oracle, Microsoft SQL Server, and IBM DB2) to modern distributed SQL databases that align with their overall cloud-native architecture. Distributed SQL is an emerging category of relational databases that combines the core benefits of traditional SQL and NoSQL systems by providing relational data modeling, ACID transactions, and strong consistency as well as cloud-native resiliency, horizontal scaling, and geo-distribution. Distributed SQL databases automatically replicate and distribute data among these servers, which can all handle read and write queries.

This change is underway now. Companies are already moving away from monolithic databases that have technical limitations in terms of scaling, resilience, and geo-distribution, as well as high license and operational costs. Distributed SQL databases deliver a modern data layer for existing applications to bridge current digital transformation initiatives and support cloud-native applications and microservices.

By deploying a modern database that offers low-cost adoption and a flexible, open architecture, enterprises can power business-critical transactional applications while remaining agile enough to adapt as needed.

Trend #2: DataDevSecOps will become top of mind

A few years ago, we saw the expansion of DevOps to DevSecOps as security was integrated into every phase of the software development life cycle, from design and development to testing, deployment, and delivery. Now, as organizations rely on data for innovation and technical differentiation, they need to ensure their data will be protected in the cloud should a failure or outage occur. This means bringing data architecture and design into the DevSecOps approach, left-shifting the design, deployment, and delivery of data early in the software life cycle.

This becomes even more important considering the increased need for robust data security and privacy, along with resiliency and availability. Security controls can’t be left to the very end -- when a solution is ready to launch. They need to be incorporated throughout the development process. DataDevSecOps ensures a data architecture that drives innovation with best-in-class security.

Trend #3: Market uncertainty will force developers to enhance skill sets

Recent layoffs in the technology sector are a stark reminder of how quickly market conditions can change. Although uncertainty is likely for the foreseeable future, the demand for highly skilled talent to fill growing skills gaps will not change.

IT professionals should focus on enhancing their developer skill sets to ensure they can stand out from the crowd and develop their careers. In-demand skills include:

  • Transferable/general-purpose skills. Professionals shouldn’t limit their focus to proprietary technology. They should learn skills and languages that are widely needed and in high demand. SQL is a great example of a popular language that developers and data scientists should know.

  • Cloud computing. Understand how to take advantage of cost-effective infrastructure and XaaS offerings.

  • Open source (Git/GitHub). Learn versioning controls and work with the larger ecosystem of open source vendors.

  • Modern database concepts. Modern application requirements for scale, resilience, geo-distribution, and cloud availability mean professionals must be aware of what’s now possible in cloud-native databases to simplify and accelerate app development.

  • Soft skills. Have an open mind when learning new soft skills and the courage to push past the status quo. Fortunately, plenty of free courses and training programs are available online to help developers and database specialists enhance these skills that can help them drive change and lead organizations to embrace new technologies.

Organizations Need to be Proactive and Prepared

There is no way to accurately predict what the future will hold, but that doesn’t mean IT organizations should sit passively and wait for events to unfold. The key is to be proactive and prepare for possible outcomes. That way, companies won’t be caught off guard.

If organizations embrace database modernization, invest in DevSecOps, and improve developer skills, they will be well-positioned to remain competitive and innovative even in the face of uncertainty.

About the Author

Karthik Ranganathan is the co-founder and CTO of Yugabyte, the company behind YugabyteDB - the open source project delivering a distributed PostgreSQL database for modern applications. Karthik has played a key role in driving distributed SQL database adoption and bringing together NoSQL and SQL capabilities into a single relational database. Before Yugabyte, Karthik was one of the original database engineers at Facebook, responsible for building distributed databases like Cassandra and HBase. He is an Apache HBase committer and was an early contributor to Cassandra before it was open-sourced by Facebook.

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