Channel 4, one of the UK's most popular television networks, recently won an award in the "Best Technical Innovation" category at the Online Media awards. The website awarded called Scrapbook is a place to tag and collect content from the Channel 4's TV shows, was built with MongoDB in just 19 weeks.
Read the full writeup on CBR Online
Big Data Is The New Normal
Now Big Data has even won a Gartner Seal of Approval, so to speak, with the publication of a new report that says Big Data is on the fast track to maturity and by 2016 it will just be data. The huge idea here is that as information goes cross-platform and vaults up in volume, very shortly Big Data will become another norm of how business gets done. By no means will all data be Big Data - that would make no sense because there of course are key values found in certain, specific data warehouses that are quite small and structured. But there also is the fact that, suddenly, business realizes it is awash in data and it knows that if only it can harness the insights that can be derived from the information already on hand or soon to be, great value will ensue. Big data transforming bricks + mortar retailing Think about the recent New York Times story about how pioneering retailers are tracking customer behavior by monitoring cellphone signals -- WiFi in particular. The story triggered significant teeth gnashing by privacy proponents, and these concerns are understandable. But a reality is that e-commerce players already have enormous tracking data on their customers and it stands to reason that, finally, bricks and mortar retailers would want to level the playing field. Big data plus smartphones is an equation that works. Put the privacy debate aside. Think simply about the information flow, its volume and the insights it would give retailers. That is very big data indeed and the goal would be mashing it up and then reinventing store layout, product placement, and in effect making it easier for consumers to find and buy what they came into the store for. Really knowing the customer Probably a gold standard for pursuing BIg Data is Netflix, which is well known for gathering information about what their customers watch but also how they watch it - where do they fast forward, where do they rewind, when do they simply turn off a film and never return? But then Netflix goes farther with its data, per reporting in SiliconANGLE : “[Netflix] actually [is] putting that data to use. Netflix has begun to produce its own original TV shows, and to do so its leveraging all of its data to do it. Netflix used its data to decide that the BBC’s ‘House of Cards’ was the best fit for a remake, and its data also correlated fans of the original to fans of actor Kevin Spacey and director David Fincher, which in turn was what led to them being hired.” Think about the power there: Big data is driving complex decisions and, apparently, it is helping get closer to what consumers really want. The maturation of Big Data A safe bet is that such stories - revolutionary as they sound in 2013 - will seem commonplace within a very few years because, right now, the ingredients are all coming together for a flowering of Big Data into an everyday business tool and probably 2016, as Gartner predicts, is as good a guess as any. Certainly it will become more commonplace in many more businesses very soon, about now in fact as the first generation pioneers - with their massive data stores and new analytical tools for rapidly making sense out of them -- start to enjoy differentially superior results. They are demonstrating that Big Data works, period. It’s no longer a computer science project, it’s becoming just plain business. The irony is that when Big Data becomes humdrum - when it loses its buzzword status - that is when it genuinely will have solidified a role as a transformational information utility. By, say, 2020 we will look back and be puzzled at how organizations arrived at their marketing and design decisions without Big Data. It will seem every bit as puzzling as, say, how organizations maintained customer data befor CRM (can you say 3” x 5” card?). From where we sit in 2013, that future seems distant indeed. But it also is closer than we think.
Splitit & MongoDB Atlas: Racing to Capture a Global Opportunity
Splitit is a global payment solution that allows businesses to offer installment plans for their customers. Unlike with other buy now, pay later (BNPL) solutions, Splitit shoppers can split their online purchases into monthly installments by using their existing credit, without the need for registration, application, or approval. “We have a very different proposition than others in this space,” says Splitit’s CTO, Ran Landau. “We’re not a financing company. We utilize the customer’s existing credit card arrangement, which allows us to accommodate smaller average deal values and a broader range of installment schedules.” Splitit works with online retailers across all market sectors and diverse price points, and recently raised $71.5 million in investment to fund global expansion. Following its IPO in January 2019, the business had seen strong growth as more consumers moved from brick and mortar to ecommerce. Then COVID-19 hit, and online shopping boomed. Landau recognized that the company needed to quickly scale its infrastructure in order to capture this large opportunity. The Need for Speed Landau joined Splitit in May 2019 and worked to modernize the company’s infrastructure. At the time, the team was using a traditional relational database. “As tech leaders, we need to make the right decision,” he says. “When I came to Splitit, I knew I needed a powerful NoSQL server so that my developers could develop faster and so that we could scale – both things that our relational databases were failing to deliver.” In the interest of getting up and running quickly, Ran’s team thought that they could move faster using a cloud-provider database that mimicked MongoDB functionality. He had used MongoDB before and saw that this solution offered the same drivers he was familiar with and claimed compatibility with MongoDB 3.6. Initially, the new solution seemed fine. But as the team started to migrate more data into the database, however, Landau noticed a few missing features. Scripts for moving documents from one collection to another were failing, and overall performance was deteriorating. The application became slow and unresponsive even though the load on the database was normal. “We were having issues with small things, like renaming collections. I couldn’t search or navigate through documents easily,” recalls Landau. Offline Database: A Breaking Point Then one day, the application was unable to communicate with the database for 20 minutes, and when the database finally came back online, something wasn’t right. Landau contacted support, but the experience was not very helpful. “We were not pleased with the response from the database vendor,” he explains. “They insisted that the issue was on our side. It wasn’t so collaborative.” Fortunately, he had taken a snapshot of the data so Splitit was able to revert back to an earlier point in time. But the incident was troubling. Other teams also had been complaining about how difficult it was to debug problems and connect to the database successfully. Landau knew he needed to find a better solution as soon as possible. MongoDB Atlas: A Reliable, Scalable Solution Landau believed that MongoDB was still the right choice for Splitit, and investigated whether the company offered a cloud solution. He discovered MongoDB Atlas and decided to give it a try. “The migration to MongoDB Atlas was so simple. I exported whatever data I had, then imported it into the new cluster. I changed the connection strings and set up VPC peering in all of my environments,” says Landau. “It was incredibly easy.” Not only was MongoDB Atlas built on actual MongoDB database software, but it was also secure, easy to use, and offered valuable features such as Performance Advisor . “It can tell you which indexes need to be built to increase speed. It’s such a powerful tool — you don’t need to think; it analyzes everything for you,” explains Landau. Another great feature was auto-scaling. “My biggest concern as I scale is that things keep working. I don’t have to stop, evaluate, and maintain the components in my system,” says Landau. “If we go back to doing database operations, we can’t build new features to grow the business.” Auto-archival Made Easy with Online Archive As a business in the financial services industry, Splitit needs to comply with various regulations, including PCI DSS . A key requirement is logging every transaction and storing it for auditing purposes. For Splitit, that adds up to millions of logs per day. Landau knew that storing this data in the operational database was not a cost-effective, long-term solution, so he initially used an AWS Lambda function to move batches of logs older than 30 days from one collection to another periodically. A few months ago, he discovered Online Archive , a new feature released at MongoDB.live in June 2020. With it, Landau was able to define a simple rule for archiving data from a cluster into a more cost-effective storage layer and let Atlas automatically handle the data movement. “The gem of our transition to Atlas was finding Online Archive,” says Landau. “There’s no scripting involved and I don’t have to worry about my aging data. I can store years of logs and know that it’s always available if I need it.” Online Archive gives me the flexibility to store all of my data without incurring high costs, and feel safe that I won't lose it. It's the perfect solution. Ran Landau, CTO, Splitit With federated queries, the team can also easily analyze the data stored in both the cluster and the Online Archive for a variety of use cases. Ready for Hypergrowth and Beyond Looking back, Landau admits that he learned his lesson. In trying to move quickly, he selected a solution that appeared to work like MongoDB, but ultimately paid the price in reliability, features, and scalability. You wouldn't buy a fake shirt. You wouldn't buy fake shoes. Why buy a fake database? MongoDB Atlas is the real thing. Ran Landau, CTO, Splitit Landau is confident that his investment in MongoDB puts in place a core building block for the business’ continued success. With a fully managed solution, his team can focus on building features that differentiate Splitit from competitors to capture more of the market. “We saw our growth triple in March due to COVID-19, but the sector as a whole is expanding,” he says. “Our technology is patent protected. Everything we build moving forward will be on MongoDB. As a company that’s scaling rapidly, the most important thing is not having to worry about my scaling. MongoDB Atlas takes care of everything.”