How AlloyDB unifies OLTP and OLAP workloads for Tricent

Editor’s Note: Tricent Security Group A/S, a leader in file-sharing security, faced efficiency and performance challenges with their PostgreSQL database infrastructure. Their OLTP workloads needed to process millions of real-time updates efficiently, while their OLAP workloads needed faster query performance to handle complex analytics. Moving to AlloyDB for PostgreSQL helped transform Tricent’s database operations, resulting in faster query response times and the ability to handle up to 250 million daily transactions. With AlloyDB’s high availability and scalability, Tricent not only solved its performance issues, but also positioned itself for future growth.

At Tricent Security Group A/S, we keep digital workspaces secure. As the CPTO, I lead our engineering, product, DevOps, and SecOps teams in the navigation of an evolving threat landscape. To that end, we’ve developed a suite of tools that help companies manage their shared files with comprehensive visibility, efficient bulk file management, and automated governance.

As cyber threats become more sophisticated, there’s a greater need for scalable security solutions like ours. In fact, our customer base has expanded significantly over the past few years, which means our database needs have grown. However, our previous PostgreSQL setup was managed on a regular VM, making it difficult to manage vacuuming processes that clean up old versions of updated or deleted records. On top of that, our previous setup’s excessively large data footprint used wide tables with many columns, significantly limiting performance.

We needed a database solution that could keep up with our ambitions — one capable of efficiently managing both our online transaction processing (OLTP) and online analytics processing (OLAP) workloads. Our OLTP challenges were rooted in needing to process millions of real-time updates, such as frequent changes to file-sharing permissions, without causing latency for customers. On the OLAP side, we needed fast performance for complex analytical queries, particularly for our ‘Insights’ product, which required deep analysis across large datasets. Our previous system’s performance lagged under this dual workload, limiting our scalability and response times.

AlloyDB syncs up with our database needs

When we started looking for a new database solution, AlloyDB for PostgreSQL quickly rose to the top of our list. Its compatibility with our existing PostgreSQL setup meant we could migrate without changing our database code at all — a significant advantage given our rapid development pace.

The migration process was notably smooth. AlloyDB provided an immediate performance boost, particularly for our resource-intensive OLAP workloads. With its columnar engine, SQL query processing for scans, joins, and aggregates became significantly faster, enabling us to handle demanding analytical queries. The columnar engine’s ability to automatically reorganize data into a column-oriented format without manual intervention was especially valuable for us. This has reduced query execution times while simultaneously improving the efficiency of our insights and analytics tools.

AlloyDB’s unique architecture separates compute and storage, giving us the flexibility to adapt quickly to changing demands. For instance, when we recently hit a performance bottleneck in our primary database instance, we were able to double our vCPU and RAM resources promptly. This gave us the breathing room we needed while we optimized our queries and code. Once we’d improved efficiency, we easily scaled back down. This kind of elasticity is invaluable when dealing with unpredictable workloads and rapid growth.

AlloyDB didn’t just solve our immediate problems, but it also opened up new possibilities. With our database concerns significantly reduced, we could focus more on what we do best: innovating new security solutions for our customers.

File under “success”

The switch to AlloyDB has also been transformative for our operations. Handling both our OLTP and OLAP workloads, it sits at the core of our architecture. For OLTP, it efficiently processes millions of real-time updates from our customers’ file-sharing activities, ensuring these are reflected without adding latency. On the OLAP side, the columnar engine boosts performance for our most complex analytical queries.

Meanwhile, AlloyDB’s scalability lets us optimize our costs without compromising on performance or reliability. Our system now processes approximately 250 million transactions per day without breaking a sweat. We see a month-over-month savings between 10% and 25% when factoring in the increased efficiency in our operations. The managed service model means less time worrying about infrastructure and more time focusing on innovation. In short, it’s allowing us to push the boundaries of what we can offer, scale with confidence, and continuously improve our services. 

AlloyDB will continue to play a pivotal role in our growth. Our vision involves deeper integration with Google Workspace and its comprehensive suite of APIs. We’re also excited about the potential to use more of Google Cloud’s AI and machine learning capabilities. With AlloyDB’s tight integration into the Google Cloud ecosystem, we see opportunities to enhance our threat-detection capabilities and provide even more insightful analytics to our customers.

Ready to get started with AlloyDB in your own environment? Check out the following resources:

• Discover how AlloyDB combines the best of PostgreSQL with the power of Google Cloud in our latest e-book.

• Try AlloyDB at no cost for 30 days with AlloyDB free trial clusters!

• Learn more about AlloyDB for PostgreSQL.