The Data Dilemma: Why We Need a New Approach to Managing Information

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Do you ever get frustrated when an app or website is slow to load new information? You want real-time updates but instead you stare at a spinning wheel as you wait for data to refresh. Companies feel this same frustration as they try to gain insights from all the data they collect. The way databases are designed today creates a dilemma where businesses must choose between having consistent up-to-date data versus easy access to their information from anywhere in the world. It’s like trying to eat soup with a fork – the tools we currently have just aren’t well suited for the task at hand. But a new approach promises to solve this data dilemma, providing fast access to reliable, global data to power real-time decision making. Read on to learn more!

The Limitations of Existing Databases

To understand why we need something new, let’s look at some of the popular databases used today: SQL databases (like Oracle) are optimized for structured data, like tables with predefined columns and rows. They allow complex queries to analyze information in sophisticated ways – like a fork that’s great for stabbing individual pieces of food. But SQL databases only run in a single data center location. Expanding globally requires complex updates. It’s like asking your little brother to run back and forth bringing you spoonfuls of soup from the kitchen – workable but really inefficient! NoSQL databases (like MongoDB) feature more flexibility and scale across data centers with less difficulty – the storage equivalent of a spoon that nicely scoops up liquid-y data. But they lack SQL’s ability to relate data sets together into a larger pool of insights. Going back to our soup metaphor, it’d be like having an oversized spoon that can carry lots of soup but struggles to pick up chopped veggies and meat floating in the broth. Neither traditional SQL nor NoSQL databases provide the complete package of features needed for today’s data-intensive landscape. It’s like trying to eat chunky soup with only a fork or spoon – difficult and messy!

The Data Dilemma

As companies accumulate more data from more locations and sources – your mobile app, website interactions, connected devices like smart speakers, etc. – they need to be able to access and analyze that information quickly to keep up with customers. Think about how Uber matches ride requests with drivers in real-time based on location data. That’s not possible if Uber’s databases take even a few minutes to update. We need systems designed for data in motion! But here’s the dilemma – businesses also need consistency across their operations. All regional offices should see the same client information rather than totally disjointed data. We can’t have Uber riders in LA requesting a trip using one version of the app while New York passengers leverage different features. Traditional databases force you to choose between having all data globally available at a moment’s notice or having 100% consistency, reliability, and control. It’s like trying to get soup to your starving family members spread across the world by instant teleportation (but some bowls have better broth and chunkier bits) or in a single flawless batch that takes ages to redistribute. Neither works that well!

Why We Need a New Approach

What we really want is soup that’s consumable the moment you want it AND consistent in each bowl wherever it’s served – a database system providing both instant access and trustworthy information. Tall order, but that’s what Fauna promises to deliver. You might think of Fauna as the souped-up food transporter from Star Trek – able to deconstruct soup and flawlessly recreate it on demand across vast distances. They call their approach a “global system of record” and it combines the benefits of SQL and NoSQL databases. How so? First, it’s built to scale easily across data centers thanks to its distributed infrastructure – sort of like having Star Trek transporter stations prepared all over the world. Your data is available for analysis from anywhere. Plus this global design actually improves consistency rather than sacrificing it. Fauna uses timing signals to perfectly sync updates across regions so you always have a single version of “truth” in your data. Uber could rely on Fauna to match a New York rider with the nearest driver by checking both their devices against the same data set simultaneously. On top of this distributed topology, Fauna offers native support for varied data types like SQL tables, NoSQL documents, and graph structures. You get powerful relational capabilities to connect related data points while also tapping into the flexibility of unstructured data. Harkening back to our chunky soup analogy, Fauna finally provides a complete “spoon + fork” utensil to handle any datatype you throw into the mix! And it does all this without requiring a PhD to set up or change databases as needs shift. Fauna was built on developer experience from the ground up. The interfaces used to build and interact with Fauna adapt based on the audience – no need to concern your soup slurpers with transporter Room B maintenance schedules! Bottom line – whether your goal is creating real-time user experiences, powering intelligent apps on edge devices, or piping insights from IoT sensors into a data lake, Fauna promises spoon + fork database functionality at web scale. Their multi-model approach serves data on demand everywhere while keeping it reliable and secure.

Exploring Potential through Web3

The article I summarized focuses narrowly on fixing enterprise database woes to enable better operational and analytical applications. But applying a spoon + fork database like Fauna in concert with cryptography, decentralized identity management, microservices, and other Web3 technologies starts to paint a picture of more than just rich data apps. It hints at entirely new potential business models, customer experiences, and market dynamics yet to be explored. Imagine frictionless transactions powered by programmable money behind the scenes…embedded recommendation algorithms that evolve based on real-time environmental variables…or platforms allowing creators and consumers to securely connect peer-to-peer. As the bandwidth bottleneck gets solved for moving swaths of data globally at speed, our creativity shifts to applying information in new paradigm-shifting ways. Just as the web stacking HTTP, HTML and browsers on top of the mature TCP/IP protocol brought about Dot Com mania, too few of us can conceive all that’s possible on top of a global reliable datastore today. Yes we may fix some enterprise problems with this new database model but likely we’re just beginning to glimpse the innovations it could unlock across industries and spheres of life. Exciting times ahead! I highly recommend reading the full article I summarized above at siliconANGLE to better understand the technical architecture powering this real-time reliable vision. The experts quoted dive deeper on overcoming limitations around database choice tradeoffs, distributed system design, and more. It’s a great peek behind the curtain! And reach out to me on Twitter @johnson_dan if you have thoughts on the coming disruption once we solve these data infrastructure challenges – whether Web3-related or otherwise! The possibilities seem endless…what do you envision?