Leveraging Distributed SQL in the Digital Transformation Journey
The Digital Path
There is no doubt that many industries and companies are suffering transformations. This is great for us, end customers of telecommunication services or as frequent buyers of our favorite supermarket. In this digital transformation, companies are providing customized services, anywhere, from our mobile devices. Cloud-based solutions, IoT, more and more data, analytics and AI, among others current and future technologies are the foundation of the digital era. Modernization, transformation and new business models are top 1 priority for organization of all industries.
It doesn’t matter whether it is a digital-native company with an ecosystem approach or an incumbent - traditional - organization executing a digital transformation initiative, data is a pillar to support the digital business. The more digital companies are or become, the more data-centric they are. Platforms, the new place to exchange value in the digital era, allow companies and organizations to capture data points from customers, partners and providers that are part of those ecosystems. It is simply inconceivable not to think about and leverage data in this transformation process.
The most valuable companies in the 2023 years, Amazon, Microsoft, Alphabet (Google), Meta and Tesla, just to name a few, they do use data and analytics at scale. Smart cars offered by Tesla models have hundreds of data points to deliver a self-driving experience. Meta uses social network interaction to provide ad-hoc marketing campaigns. Netflix gives better recommendations for movies and series than our best friends. Surprisingly or not, the companies mentioned above are categorized as digital born, whether they transformed or were digital-native from the ground up. No matter how these companies became digital born, data is a first-class citizen.
A Data-centric World
Every interaction in the digital ecosystem is an opportunity to learn and improve the business. The digital customer demands customized and timely services and products, in exchange for the data they provide. It is a fair deal for both sides of the ecosystem. For that, companies should understand the customer journey, capturing all the touch points and interactions, delivering the experience they are looking for. This is also known as “segment of one” in the marketing field, evolving from industrial methods to categorize and fit customers into groups or general populations. Recognize customers behave differently nowadays.
Data is of paramount significance to create the digital experience. Being the raw material for Analytics and Artificial Intelligence, companies expect to embed more and more data into their digital platforms and enhance the customer journey with service customization, ad-hoc recommendations and added-value products. Not only the customers will benefit from that data, but also the integrated SCM - Supply Chain Management - including providers and partners. In the era where traditional and pre-established managerial practices are challenged, data arises as a primordial and strategic asset for any company
Data is the blood running?through the veins of?digital companies
Databases in the Digital Era
In the past 10 to 15 years, a lot of innovation and new technologies were developed, promoted and adopted for the Analytics side of the data. Apache Hadoop, a popular open source project, was a key milestone in the Big Data era, enabling companies to store, analyze and serve petabytes of data for Business Intelligence and more recently, AI use cases, and helping companies to understand customer behaviors, improving forecasting and setting the basis for a cross Enterprise Intelligence practice. Cloud computing recently also helped to add scalability for data analytics platforms, at the same time decreasing the maintenance burden and TCO of legacy solutions.
But what happened to the transactional platforms, commonly known as OLTP or RDBMS? Most of the companies are still relying on traditional transactional databases, lacking real innovation for years - maybe decades. Most of those solutions - mainframes for example - were “lift and shifted” to run on Cloud Service Providers - CSP - but are not taking full advantage of what cloud can provide, like containerized compute and elasticity. Here is where Distributed SQL makes the difference.?
Built in from scratch, leveraging new architectural approaches, the new set of database technologies overcome the limitations and issues inherent of traditional transactional databases. By leveraging on-demand compute resources, Distributed SQL solutions are able to scale at million user concurrency, spread across global infrastructure to provide unique resilience and high-availability capabilities, setting the basis for critical and data-centric digital applications at almost zero-ops cost.
The STAR principle
The advantages of cloud-native computing is clear for the C level of any organization. Flexible on-demand resources provisioning, innovation acceleration and enhanced TCO are observed as the main drivers to rethinking the IT strategy and move to cloud. In regards to where data is managed for applications, databases in the era of Digital Transformation need to address and overcome limitations inherent in traditional databases solutions, specially the capability to easily scale while keeping performance and SLAs.
In the 4th industrial revolution, technologies are considered business enablers and the STAR principle helps to summarize all the capabilities companies are demanding from transactional databases when building digital services and products. STAR stands for the initial letter of Scalable, Trustable, Autonomous and Resilient, which are the features and functionalities any cloud-native solution is meant to provide.
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Scalable
The digital era is about scalability, which means rapidly going from an idea to prototype, scaling to thousands of users and customers in a short period of time. Any new applications or enhancement of current features, are opportunities to know more the customers, and those data points should be captured and recorded. At the same time, databases should be able to scale accordingly with the service demand and all the actors of the digital platforms are interacting with each other. Scalability also allows companies to prototype with minimal costs at the beginning, opening up for more innovation and “out-of-the-box” ideas to be easily and quickly tested. At a global scale, some companies will require data to be closer to their final customer, regardless if it is a shopper based in Austin, Madrid or Tokyo.
Trustable
Reliability is fundamental for companies running critical and customer-facing workloads and applications. They want assurances that transactions are recorded, stored and be ACID-compliant at all times even with thousands of operations and customers concurrently using their digital platform. The digital market can rapidly scale from an MVP product to a massive audience from one day to the next, but data consistency and security is mandatory during the product maturity lifecycle. Even though databases are distributed globally and some cloud provider regions are down, the whole system needs to guarantee consistency and correctness.?
Autonomous
Focus on innovation, not operations. In other words, stop firefighting. Digital is about reimagining traditional business models and creating new things fast, so it is relevant to IT teams to have enough time to innovate at that pace, avoiding or minimizing operational burden. Cloud-native solutions have embedded this “easy to manage” approach, enabling companies to quickly spin up new infrastructure and services to speed up innovation. Furthermore, with zero-ops capabilities, a database can scale up and down to keep up with demand, requiring less effort from administration teams. And as digital services are always available 24x7 from anywhere, companies cannot suffer major disruption for maintenance, like upgrades and backups. With no downtime rolling upgrades based on containerized architecture, upgrades should be effortless and painless, with minimal impact for final customers.?
Resilient
Distributed architectures are the best solution to address scalability issues, but at the same time presents challenges. As distributed databases are spread across multiple nodes or servers performing small operations - computing and storage - but combined works as a single logical service, the platform should handle a myriad of possible issues, like server failures, network outage, write and read concurrency, just to name a few. Now imagine a multi cloud strategy, which is the approach many companies are adopting to minimizing risks, avoiding vendor lock-in, and getting prepared for new regulations - like DORA in EU for instance. Digital companies require resilient data infrastructure, but without all the complexity of managing and operating distributed systems. Assurances of data availability and consistency at any incident or service disruption is mandatory to innovate fast and securely manage data-centric applications.
CockroachDB, a cloud-native database
Cockroach Labs brings together all those previous requirements and needs mandatory for databases to help companies in the Digital Transformation Journey. As companies are seeking to innovate and transform their business models, data is taking more relevance when defining a digital strategy. Data-driven companies will enable new customers experiences and service customization, strengthen their relationships and advocacy. Companies from different industries are relying on Cockroach Labs to start small, scale fast and innovate always.
Here are the main features of CockroachDB:
CockroachDB will help companies to properly improve or set the basis for the following Digital pillars:
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