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How to decide between SQL, NoSQL, or NewSQL

There's an adage that states, "In any moment of decision, the best thing you can do is the right thing, the next best thing is the wrong thing, and the worst thing you can do is nothing." The rapid pace of today's technological advancements and the torrent of data that floods your system daily makes this statement all the more poignant. As data experts, we're at a pivotal intersection in our data management journey. Three paths stretch out before us - SQL, NoSQL, or NewSQL - each with its own potential rewards, risks, and challenges.

Here you are, staring down each path, trying to discern which one to embark on. It's like being in the middle of a vast and complex data universe, attempting to chart your course, weighing up nebulous benefits and potential pitfalls. This decision isn't just about choosing a database type. It's about shaping the future of your data infrastructure and, by extension, influencing how your organization operates, competes, and innovates in a data-driven world.

Choosing the right database technology can enhance your performance, facilitate effective data management, enable robust security, and support future scalability. On the flip side, a poor choice can lead to performance bottlenecks, system instability, security vulnerabilities, and eventually, unhappy stakeholders. That's the nature of the game when dealing with something as integral as data. The stakes are high.

The magnitude of this decision is further amplified by the pace of change. Technological evolution doesn't hold its breath while you ponder your options. New technologies, updates, and approaches pop up faster than you can say 'data model', each promising to be the magic bullet that solves all your data woes. In this dynamic landscape, you need to make an informed decision, and make it fast. But that's easier said than done.

It's not a question of simply going with the new and shiny or sticking to the tried-and-true. It's about understanding your unique needs and constraints, sifting through the noise, and picking the technology that fits your requirements like a glove. SQL, NoSQL, or NewSQL? It's time to roll up your sleeves, dig deep, and chart your course through this data universe.

As we begin our exploration, let's start by understanding each path and its unique characteristics.

SQL: The Old Reliable

In the world of database technology, SQL stands as the traditional stalwart, the equivalent of a trustworthy, old map that's guided countless explorers before you. SQL, or Structured Query Language, is the language used in relational databases. They're built upon a structured schema, requiring a clear definition of tables, fields, and relations before storing data.


SQL databases like MySQL, PostgreSQL, and Oracle are known for their robustness and reliability. They shine in their ability to handle complex queries, thanks to their ACID compliance (Atomicity, Consistency, Isolation, Durability). If your work involves transactions that need these properties—like financial systems, for example—SQL might be your go-to choice.

But every path has its rocky terrain. SQL databases often stumble when it comes to scalability and flexibility. They typically scale vertically, requiring more powerful hardware as data grows, and this could become costly over time. They also struggle to handle unstructured data—like JSON, images, or text documents—which are increasingly common in our data-rich world.

NoSQL: The Flexible Pathfinder

Emerging in response to the limitations of SQL, NoSQL or "not only SQL" databases like MongoDB, Cassandra, and Couchbase offer a new paradigm. They're designed to be flexible, scalable, and capable of handling vast amounts of unstructured data.


NoSQL databases don't require a predefined schema, making them highly adaptable to changing data requirements. They scale horizontally, meaning you can simply add more servers to expand your database. This makes them a compelling choice for applications generating massive volumes of data or requiring real-time responses—think social networks, content management systems, or real-time analytics.

But even the most flexible pathfinder has its limitations. NoSQL databases typically compromise on ACID compliance for the sake of scalability and performance. This can result in eventual consistency, where your data may not immediately reflect all changes. Also, given the diversity within NoSQL types—document, key-value, wide-column, graph—you may face a steep learning curve to understand their nuances and best use cases.

NewSQL: The Hybrid Voyager

NewSQL databases like CockroachDB, VoltDB, and MemSQL seek to bring together the best of both SQL and NoSQL worlds. They aim to deliver the scalability of NoSQL while maintaining the ACID compliance and structured schema of SQL.


These newer databases promise high performance and scalability without compromising the relational model and SQL's powerful query language. They're designed to work well in distributed environments, catering to the ever-increasing demands for cloud-based and globally-distributed applications.

However, the hybrid path isn't without its potential pitfalls. NewSQL databases are relatively new entrants in the database technology space, and with that comes certain risks associated with maturity and a smaller community for support. Also, while they aim to balance the best of both worlds, NewSQL might not always be the optimal choice for applications that strictly require the absolute scalability of NoSQL or the complete reliability and established history of SQL.

Having peeked down each path, the question remains: which one is right for you? Is it the reliable SQL, the flexible NoSQL, or the hybrid NewSQL? Let's move on to the next section where we will aim to provide you with a compass to navigate this decision.

Armed with the knowledge of each path's terrain, strengths, and challenges, the task now is to discern which one aligns best with your mission. This decision isn't a one-size-fits-all proposition, nor should it be taken lightly. After all, your chosen path will significantly impact your data operations and, by extension, your ability to deliver value.

Step 1: Identify Your Needs

Begin by reflecting upon your unique needs. What kind of data are you working with? Is it mostly structured, or do you foresee a growing influx of unstructured data? How crucial are real-time insights? Are you developing a product that needs to be quick-to-market, and therefore requires a database that is easy to change and evolve?

Step 2: Assess Your Scale

Size matters in database selection. A small to medium-sized application might find everything it needs in a SQL database's robustness and ACID compliance. However, if your application is designed to service a massive number of users generating colossal data, you'll likely need the horizontal scalability offered by NoSQL or NewSQL.

Step 3: Consider Your Team’s Skillset

Remember to factor in your team's expertise and experience. SQL's maturity means that many developers are comfortable with it, while NoSQL's diverse offerings can require additional learning. NewSQL, on the other hand, brings a balance but also entails working with relatively new and evolving technology.

Step 4: Align with Your Future Plans

As you stand on the precipice of this decision, you mustn't only consider the needs of today but those of tomorrow. Your choice should be able to accommodate growth, change, and the inevitability of future technological advancements.

Imagine, for a moment, you're a growing e-commerce start-up with an expanding customer base. Your application needs to handle a surging volume of data, perform real-time analytics for personalized recommendations, and seamlessly adapt to ever-evolving data requirements. After a thorough evaluation, you might find the scalable, flexible NoSQL route the most promising. Or perhaps the hybrid, distributed capabilities of NewSQL appeal more, striking a balance between maintaining transactions' integrity and supporting growth.

Conversely, suppose you're developing a financial system, where transactions' reliability is paramount, and data is primarily structured. In that case, the robust, ACID-compliant SQL path might serve you best.

And so, after a deep dive and thoughtful introspection, you will find your path. Remember, the path you choose isn't as crucial as understanding why you're choosing it. There's no universally "correct" choice, only the one that best suits your specific circumstances.

When charting your course through the vast data universe, making this decision is a key milestone but remember, the journey doesn't end here. It continues with consistently assessing your chosen path, learning, adapting, and evolving with the ever-changing data landscape. Embrace the journey, knowing each decision, each step brings you closer to unlocking the transformative power of your data.

And as always, if you want to skip the months of DIY development time and costs, our Beyond Data platform can help you today. Because we’ve already optimised our platform and can share costs across many customers, we can deliver these same features to you at a fraction of the cost.


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