What is Scalability in Cloud Computing

What is Scalability in Cloud Computing

Joel Stewart, VP of Customer Success at Pepperdata, on how Query Spotlight drastically improves the management and optimization of databases, tables, and queries in a distributed query platform–instantly reducing operating costs in the process.

Thankfully, Pepperdata Query Spotlight is a significant step forward for managing and optimizing all the databases, tables, and queries on a distributed query platform.

I have worked in big data and application optimization for years. One of the consistent features of the landscape throughout that time? Query workloads. More specifically, constantly troubleshooting and managing distributed query platforms.

For as long as I can remember, queries have been at the center of the enterprise data center. Queries remain critical to companies today, as technology has matured and evolved into distributed query platforms such as Hive, Redshift, and Snowflake. Every customer that I work with is using queries in their big data analytics stack. Customers are forecasting growth in both the number of queries they run and the amount of data stored in their distributed query platforms. 

As the systems and queries become more complex, businesses continue to demand optimized performance and faster results. To achieve these goals, database administrators and query authors spend a lot of time optimizing their architecture, data partitioning, indices, and query syntax. 

But: Even with all this time investment, the multi-tenant nature of today’s distributed query platforms often produces inconsistent performance. This leaves customers challenged to troubleshoot performance issues.

Enterprises need a solution.

Thankfully, Pepperdata Query Spotlight drastically improves the management and optimization of databases, tables, and queries in a distributed query platform.  

In Query Spotlight, database administrators and query authors are able to gain a holistic view of their databases, tables, and queries across the entire system.