How a Trading Tool FinTech Company Prepared for 10X Growth Through Amazon Aurora MySQL Assessment with Datavail

Datavail’s customer, a trading technology FinTech company, has a decades-long history of creating world-class trading tools and market connectivity solutions. Its products power trading platforms and supports FinTech disruptors through APIs and seamless integration to broker-dealers, clearing and custodian providers, market data and information content providers, as well as AML and KYC vendors.

Database Performance Needed to Scale with the FinTech Company’s Success

The customer wanted to enable the ability to scale and quickly innovate to help its financial services users grow their businesses and solve their needs. These needs ranged from entering new markets, creating new services, and streamlining current technology and operational workflows.

As part of that goal, the organization turned its attention to the performance and scalability of its multi-tenant Amazon Relational Database Service (RDS) for MySQL and Amazon Aurora MySQL Serverless production database cluster. Database configurations that work at smaller scales sometimes struggle as an organization becomes more successful, leading to negative customer experiences.

The customer used an Amazon Aurora Serverless V2 cluster, compatible with MySQL 8.0.23, with InnoDB tables in production, alongside Amazon RDS for MySQL. Queries were performing slowly, leading to complaints about critical performance issues.

Comprehensive Amazon Aurora and RDS MySQL Database Assessment and Remediation

The customer needed high-level query tuning, index recommendations, and a complete database assessment. However, its in-house team needed to keep focused on the organization’s core fintech development. The organization reached out to Datavail’s AWS and MySQL teams to leverage their specialized expertise in Amazon Aurora and RDS for MySQL.

Datavail conducted a thorough database health check of the environment to identify the root causes leading to slow queries and critical performance problems. The team also made recommendations on configuring the Aurora MySQL cluster to better support the customer’s future growth through a highly scalable, performant, and cost-effective system.

Datavail’s recommendations and best practices covered many areas, including:

• Capacity Planning: With the customer predicting a 5-10X growth in its future data growth, its databases had to stand ready for this volume. The Datavail team suggested increasing the maximum capacity of the Amazon Aurora Serverless instance to future-proof the database, along with reviewing archival policies for larger tables and considering sharding.

• Vertical and Horizontal Scalability: Besides ensuring that the Aurora databases could scale vertically, Datavail also looked for ways to improve horizontal scalability, such as adding more reader nodes and implementing RDS Proxy Read. By optimizing the use of RDS Proxy Read and auto-scaling policies, read scalability becomes more cost-effective.

• MySQL Configuration and Performance Tuning: Datavail covered several areas that would help the customer achieve the database performance necessary to keep up with its innovative solutions. The suggestions included defragmenting large tables, adjusting database session timeout values, purging unwanted data from the instance, and rebuilding the indexes often.

• Database Security: Datavail’s team reviewed the security and user settings on the MySQL databases to evaluate whether there were any areas of concern.

• Ongoing Database Assessment and Maintenance: Keeping a database cluster healthy for an innovative organization is not a one-and-done project. The Datavail team highlighted several areas to review consistently, including slow queries, growing tables, and database objects.

• Database Monitoring: To go along with the ongoing assessment process, continuous database monitoring via AWS CloudWatch or a third-party tool, such as Datavail TechBoost, would allow the customer to proactively keep an eye on its database performance.

Following the database health check, Datavail’s team began the remediation process to stop performance and scalability issues from further impacting the customer’s users.

Results

The customer resolved its database performance issues and can now prepare for its future scalability goals with Datavail’s help. The benefits this innovative fintech organization now enjoys include:

• 10X Data Growth Potential: The customer no longer had to worry about its success and resulting data volume growth outpacing its AWS database scalability.
• 50% Increased Maximum Capacity: The maximum capacity of the Aurora Serverless instance was increased, and auto-scaling in V2 is handled in 0.5 ACU increments for better cost optimization.
• 90% Decrease in Data Storage Requirement: Large fragmented tables can take up a lot of database real estate. Datavail’s expert DBAs identified an 800GB table that could be defragmented to reclaim 90% of the space, which significantly improved performance, cost, and overall data storage requirements.
• Improved Database Cost-Efficiency: By implementing the recommendations and best practices from the database assessment, the customer could reduce the costs of the cluster.
• Resolved Critical Performance Issues: Datavail’s fast remediation of the database performance problems allowed the customer’s users to enjoy a smooth and disruption-free experience.

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