We’re excited to announce a concerted effort to grow our Global Consulting Services, led by Vijay Vijayasankar, VP and GM of Global Channels and Consulting Services. Vijay has more than 14 years of experience leading consulting teams for a wide variety of enterprises across North America, Europe and Asia.
“I grew up in consulting,” says Vijay, “from TCS in the late 90s to IBM GBS just a few years ago.”
MongoDB is the next-generation database and one of the fastest growing database ecosystems, with tens of thousands of downloads of the software per day and over 650 services and technology partners. MongoDB Global Consulting Services will help organizations realize what’s possible with the database, and show them how best to build and manage their applications.
“I believe we can show customers a better path to success,” Vijay explains. “My team can do that assessment quickly. We can redesign old applications and replace them with new, modern applications that will grow with changing business needs.”
We are now hiring consulting engineers. If you are an expert in building apps on MongoDB and/or operating database clusters in complex landscapes, and love to work closely with clients, please let us know at https://www.mongodb.com/careers.
For more information on MongoDB Consulting packages, click here. Stay tuned for much more news to come.
MongoDB Connector for Hadoop Now Certified with Top 3 Hadoop Vendors
We’re excited to announce that our MongoDB Connector for Hadoop has just been certified on MapR’s latest distribution, 4.0.1 . The connector, which allows customers to use MongoDB as an input source and/or output destination for Hadoop deployments, is now certified on distributions from all of the leading vendors in the space, including MapR , Hortonworks , and Cloudera . As an operational database for use cases such as Single View , Internet of Things , Real-Time Analytics , and more , MongoDB is the perfect technology complement to Hadoop. With the connector, live data from MongoDB can be brought into Hadoop, enriched through analytics (often with data from other sources), and then passed back into MongoDB to better serve user-facing applications. Orbitz, the travel booking company, uses MongoDB and Hadoop together to deliver real-time pricing and compete for travel shoppers. MongoDB serves as the data collector while Hadoop is used to store and analyze the data. The City of Chicago built a futuristic predictive analytics platform using MongoDB and Hadoop Their WindyGrid system allows officials to access a real-time view into crime, public health and other citizen issues. Data analysis allows the city to predict disease outbreaks and decide in real-time where to place first responders. Other Common Use Cases That Leverage MongoDB + Hadoop Ecommerce MongoDB can be used to... Hadoop can be used to… Store products, inventory, customer profiles, clickstream data Run real-time recommendations Session management Detect Fraud Store complete transaction history, and clickstream history Build recommendation model and fraud detection models Insurance MongoDB can be used to... Hadoop can be used to… Store insurance policies, customer web data, call center data, demographic data Real-time churn detection Conduct customer action analysis Create churn prediction algorithms Learn more about how Hadoop and MongoDB can work together [here](http://www.mongodb.com/hadoop-and-mongodb). What’s next? Get started by checking out the documentation on the MongoDB Connector for Hadoop or learn more at one of our upcoming MongoDB Days: MongoDB London , 11/6; MongoDB Munich , 11/12; MongoDB Paris , 11/18; MongoDB Beijing , 11/22; and MongoDB SF , 12/3.
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.”