Results from the State of Enterprise Database Deployments in 2019
For the second year in a row, we worked with Dimensional Research to conduct an important survey of application developers, application release engineers, enterprise architects, and DevOps engineers. These are the people on the front lines of database release issues. They work on mission-critical applications at enterprises for applications you use every day. It’s a tough job balancing the pressure (90% report they are feeling pressured to release database changes faster) while minimizing potential downtime and guarding against security issues.
Once again, survey participants are telling us that there is a problem that needs to be solved. The state of enterprise database deployments in 2019? It feels like a cry for help.
Constant Manual Database Rework
The majority of the survey group spends hours, even days, manually reviewing and validating database change scripts. They manually review and fix any schema change issues, too. A vast majority (91%) report that they have to rework database changes multiple times before they are ready to deploy to production. Not only is this probably not how they would like to be spending their time, but it’s also a very costly way to spend their time. Think about it: DBAs typically make $150k+/year. Instead of data modeling and improving indexing strategies that can dramatically improve the efficiency and performance of the database, they are manually reviewing change scripts. This doesn’t have to be the case.
Removing Manual Database Tasks
It’s 2019! We live in a world of amazing automation. There are database automation tools that check for common mistakes and helps application developers write better database code. There are tools that help DBAs set specific rules for common issues. These tools work a lot like application code automation tools that help catch errors before they get committed.
Automating Database Deployments Makes Sense
Captain Obvious results from our report:
- 92% say increasing automation for database deployments would accelerate overall application release cycles.
- 96% of organizations would benefit from automating database deployment processes.
Brace Yourselves. Database Automation is Coming.
Database automation can sound a bit scary to professionals whose job is to guard against threats to one of their company’s most prized possessions: data. It’s good to be guarded! But the last two surveys we’ve sponsored (and countless other state of DevOps reports) all shine a light straight at the problem; the database is the next area of focus in the quest to move application releases faster. It’s not possible to squeeze any more productivity out of teams without using the right kind of tools along with an updated process. (Preferably one built on Agile DevOps principles, like Liquibase.)
The Robots Will Not Replace You
The database team isn’t getting replaced. They’ll just be able to work on more important issues, such as:
- Architecture planning
- Getting ahead of usage spikes
- Data science
- Machine learning
There’s still a lot of work to be done around the database. Your robot friends help with the tedious, manual tasks so you can bring much more value in other ways. For motivated and dedicated database developers and DBAs, database automation opens up a lot more opportunities to focus on the cutting edge instead of the mundane. Data is the future! It’s amazing. Don’t spend it scanning logs and reworking database changes over and over again.
Check out the full report:
Automate BigQuery schema change and version control with database DevOps
Google's BigQuery is a fully managed, serverless cloud data warehouse, or database as a service (DBaaS), that brings unparalleled scalability and convenience to data analytics.