November 2022 Summaries

YugabyteDB, the first distributed SQL database to achieve AWS Graviton Ready status, has successfully optimized its performance with the new ARM-based processors, providing a 20% cost savings compared to existing EC2 instance types. By testing and optimizing YugabyteDB on Graviton-based instances, the company was able to deliver equivalent throughput while reducing costs. The journey involved adding features that supported the ARM architecture, benchmarking performance, and implementing optimizations such as compiler flags and operating system changes. With the success of this partnership, customers now have more options for choosing between platforms and chipsets, allowing them to select the best fit for their unique needs and preferences.

yb_stats is a tool used to obtain YugabyteDB cluster status, providing runtime information in a single location. It gathers facts from every YugabyteDB cluster component and stores them in a "snapshot" at a single point in time, storing metadata only and not actual user data. The snapshot contains various performance counters, gauges, histograms, and other metrics for masters and tablet servers, as well as YSQL level performance counters, statement performance data, node_exporter counters, and more. yb_stats has two main goals: to fetch available information in one go and eliminate the cycle of investigation and data collection. The tool stores cluster data in CSV files, allowing for manual investigation and loading into a database. It also provides ad-hoc mode for testing and snapshot-diff mode for comparing snapshots over time. Additional benefits include validating version information after upgrades and enabling further print options to customize output. yb_stats is useful for troubleshooting, analysis, and support, providing persistence and security for the collected data.

As we enter 2023, the database market is poised for a significant shift towards modern, distributed SQL databases that align with cloud-native architectures. Companies will prioritize cost and value, embracing open-source solutions and database-as-a-service offerings to drive IT efficiencies. With the rise of DevDataSecOps, data security will become a top priority, and PostgreSQL compatibility will emerge as a de facto standard for transactional databases. As market uncertainty leads to skill set enhancement, developers and database specialists will focus on skills development, training, and career-advancing technical certifications. Distributed SQL approaches are expected to gain traction, offering the freedom and flexibility required to address current and future needs.

To create an interactive data analytics dashboard in Power BI using YugabyteDB, first install Power BI Desktop and connect to your YugabyteDB database using the standard PostgreSQL connector. You can then select the tables you want to visualize and choose the storage mode for each table, which determines how Power BI handles queries and caching. The "Dual" storage feature allows you to cache data in the table while still querying it dynamically, reducing database calls and improving report performance. By leveraging YugabyteDB's distributed SQL capabilities and Power BI's visualization tools, you can create a seamless and easy-to-use dashboard for analyzing and visualizing your business data.

I joined Yugabyte as a Solutions Engineer because I was attracted to its open-source roots and cloud-native technologies, which align with my desire to work on modernizing backend systems for Japanese enterprises. My experience at MuleSoft, where I worked with legacy modernization challenges, made me realize the need for a database like YugabyteDB, which can provide scalability, microservices support, and strong consistency. I am excited to be part of a technology revolution that is changing the way databases are designed and implemented, and I believe YugabyteDB has the potential to become THE de facto distributed SQL database for cloud-native applications.

In distributed databases, hotspots can occur when data grows in one node before moving to another node, causing a single node to become a hotspot for reads and writes. To avoid this, creating an ASC index on the create timestamp can distribute the data across multiple tablets, but this method loses the ordering needed for range queries. A better solution is to implement lightweight application-level sharding, which distributes the index across multiple tablets while retaining the ordering by create_ts. This involves creating an index of the form (shard_id HASH, create_ts ASC) and specifying the shard_ids in the IN clause or as a UNION of multiple selects for range queries. By doing so, the hotspot problem is removed, and the query executor can efficiently retrieve rows from the sorted lists.

Geo-distributed applications are designed to work across multiple availability zones and regions, ensuring high-availability, performance, and compliance. To design and implement such applications, software engineers need to select the right components from the beginning, considering distribution across distant locations and scalability horizontally. The key steps involve deploying application instances across zones and regions, configuring a distributed API layer, deploying a distributed database, enabling a global cloud load balancer, and running and testing the application. A geo-distributed application must withstand various cloud outages, serve user requests at low latency regardless of user location, and comply with data residency requirements.

Distributed SQL databases have emerged as a new evolution in transactional databases, differing significantly from both NoSQL and NewSQL solutions. With its horizontal scalability, continuous availability, and multi-cloud deployment options, distributed SQL offers several advantages over traditional database architectures, including ease of use, improved performance, and reduced downtime during maintenance tasks. It is particularly well-suited for modern applications that require high availability, low latency, and the ability to move data across different environments, making it an attractive option for companies adopting a multi-cloud strategy or those looking to improve their edge computing capabilities. By providing a unified data store across environments, distributed SQL databases can help organizations overcome challenges such as application growth, always-on business, app mobility, next-gen edge computing, and microservices, ultimately enabling them to build a data-centric business that is ready for any future scenario.

A geo-distributed application is an app that spans multiple geographic locations for high availability, resiliency, compliance, and performance. It aims to withstand all types of cloud outages, including major incidents, and remain available and resilient even in the event of such outages. Geo-distributed apps help with compliance by ensuring that users' personal data can remain in the country/area of origin, addressing regulations like GDPR. Additionally, they help boost performance by providing a user experience comparable to one from a different region due to their ability to distribute data across multiple locations, reducing latency and improving overall performance.

To capture `pg_stat_statements` data from all nodes in a persistent table, set up database objects, including a table and sequence, to collect the data. The data is then captured by inserting it into the table using a PostgreSQL query. The output can be validated by querying the table for specific columns. This allows for performance analysis of queries executed on the database, providing insights into query execution times and resource utilization.