As more organizations use cloud services to store their database information, it’s also important for databases to be effectively and efficiently keep up with their data volume and growth.

Today’s cloud-transformed organizations need to build futureproof distributed SQL databases that are designed for cloud-native applications, while offering powerful feature sets and a rich ecosystem of tools and extensions.

DigiconAsia had the privilege to hear from Vish Phaneendra, Senior Director, Technology APJ, Yugabyte, to discover insights into – and examples of – how distributed SQL is changing businesses globally and in Asia Pacific.

As businesses digitalize, many have developed cloud-native applications. What are some typical challenges they face with their existing databases? 

Vish: Harnessing the full potential of data has become essential for achieving business success, prompting companies in various sectors to adopt cloud-native applications as a means of maintaining competitiveness.

As businesses digitalize, the surge in cloud-native workloads has increased demand for agility and efficiency. Organizations now require databases that can perform new and flexible functions from anywhere in the world and at any time.  

Existing legacy SQL, NoSQL, and NewSQL databases aren’t built for the needs of cloud native applications. Sure, they may have evolved to become cloud hosted, but are far from being cloud native. It is difficult (if not impossible) for applications built on these databases to take full advantage of the elasticity and geo-redundancy offered by modern cloud infrastructure and to utilize it to its maximum potential. Moreover, making these databases resilient to hardware failures requires expensive third-party replication solutions and engineering effort.

Vish Phaneendra, Senior Director, Technology APJ, Yugabyte

Faced with issues such as the high costs of operating legacy database systems, low-scalability, fragmented database infrastructures that hinder performance, and a monolithic SQL database, distributed SQL has become a popular choice among organizations looking to future-proof their business.

For example, we recently migrated the existing database systems of Tokopedia, Indonesia’s largest e-commerce platform, to a cloud-native environment. Yugabyte’s scalable distributed database, YugabyteDB, provides high scalability and resilience, crucial requirements for Tokopedia’s critical services, which handle order history and product services for 11 million merchants, and more than 100 million active users daily.

After the migration, Tokopedia was able to implement a more agile micro service-oriented architecture, improving productivity and cost efficiency.

How does an organization go about building futureproof distributed SQL databases for their cloud-native applications?

Vish: To build a futureproof data layer, CIOs and CTOs need to take a high-level strategic approach, considering evolving business needs alongside the fluid nature of data and cloud environments.

    1. Firstly, businesses need to think long-term to ensure that their databases are optimized for performance, scalability, and reliability.

      For example, while it’s important to curate a portfolio of databases that meet different business needs, implementing too many databases with similar features leads to operational and developer inefficiencies.

      The solution is to pick a multifunctional database, one with enough range to manage a broad spectrum of tasks. This database should also enable transactional consistency of data, scale, and low latency.

    2. Secondly, businesses must understand that cloud environment are prone to failures. There are many factors – hardware, software, service, and more – but the key takeaway here is that businesses should focus their energies on implementing processes and procedures that address and mitigate downtime events.

      Distributed SQL databases offers the integration of fast failover capabilities for minimal disruptions and to ensure that critical services remain highly available in the event of data center failures and regular system maintenance with zero data loss.

    3. Finally, organizations need to think ahead and plan for the ever-evolving state of data. We’re only starting to realize what we can do with data, and in the next 5, 10, 20 years, we’re going to see huge changes.

      Currently AI frameworks in cloud are still an emerging technology. But, as it matures and use-cases proliferate, businesses are going to need to consider exporting their data or connecting existing systems to an AI-based system.

      This will be an uphill battle for businesses using traditional database systems, because all their time will be spent trying to make those connections. Instead, they should be adopting a highly compatible and adaptable database, that allows for new systems to be interconnected, swapped out, and more – one with infinite adaptability built in.

When we built YugabyteDB, this was a key problem we wanted to solve. “Yuga” means an era or extremely long period of time in Sanskrit, so “Yugabyte” signifies that data lives forever without limits. As the importance of data continues to grow, we believe it’s not just the quantity of data created that matters, but our ability to reliably store that data anywhere, and access it at any time.  

What can businesses in some specific industry sectors do better with the rich ecosystem of database tools and extensions available today? 

Vish: Data is at the heart of innovation in customer experience across many industries. Businesses are transforming themselves into data-driven enterprises in order to deliver new and innovative services to their customers.

The availability of a rich ecosystem of database tools and extensions enables companies to manage and leverage their data better than ever, for tangible business outcomes.

Broadly, there are two ways that businesses can use data. They can collect and store vast amounts of data in warehouses (like Snowflake) and data lakes, and analyze the data to glean insights into business operations, customer preferences, and more. This use of data for long term analytics and decision making is called online analytical processing (OLAP). Data can also be used to enhance customer experience in real time when users interact with the company’s services. This use of data is called online transaction processing (OLTP).

Working together, OLTP and OLAP can transform digital systems. For businesses in industries sectors such as retail and finance, the data accessed by customers and generated from online banking transactions and e-commerce sites needs to be accurate, responsive, and always available to end users even in situations of cloud failures and system upgrades. In these industries, the right database tools and extensions play a vital role. Let us look at how modern transactional processing systems can be used in retail and financial services.

RETAIL: In the retail sector, businesses are increasingly recognizing the importance and value of data when generating insight into market trends. This includes making note of changing consumer behaviors and expectations, such as a shift towards ecommerce and online shopping. As the volume of data that retailers collect grows, it is crucial that they build a robust data strategy that ensures they can continue providing exceptional customer experience, while still scaling their business.  

For example, when we started working with Kroger, the largest supermarket in the US and one of the top 5 retailers worldwide, they relied on legacy database systems. Together with Yugabyte, Kroger embarked on a significant digital transformation initiative to update key customer-facing services like their shopping cart and coupon applications and deliver a localized customer experience across a whole continent. 

Kroger turned to YugabyteDB to deploy a modern data layer, which helped them to achieve single digit millisecond latency across regions with bi-directional asynchronous replication for the shopping list application. With geo-distribution, customers were served from a local cluster to reduce latency and ensure an ideal customer experience.  

FINANCE: As the world inches closer to a cashless society, digital payments have become the center of transaction processes such as account processing, digital banking, and e-commerce. In response to this growing demand, many financial institutions are now exploring ways to modernize their database and provide innovative digital solutions to facilitate payments and banking.  

However, many companies face challenges embracing the public cloud and microservices due to legacy database systems.  One example is Mindgate Solutions, a digital payment solutions company. It processes close to 3 billion digital payments monthly. With the rapid growth of Unified Payments Interface (UPI) instant, real-time payments in India, it was difficult for them to deliver horizontal scale and enable active-active setup for their critical applications while using a traditional relational database system (RDBMS).

Using YugabyteDB, a distributed SQL database, Mindgate was able to mitigate transaction loads on a single data table, reduce latency, support fully distributed ACID (Atomicity, Consistency, Isolation, and Durability) transactions and ensure database transaction validity, even in the event of system crashes, power failures, and other errors. Similarly, financial businesses and institutions can leverage these benefits of a distributed SQL database alongside advanced features such as encryption, RBAC, and flexible authentication also help ensure seamless security for data stored or transferred, ultimately improving the digital payments experience for end-users. All this results in a faster and more reliable user experience for customers making critical financial transactions.