We’re please to share Forrester Research Inc.’s recent report, “The Forrester Wave™: NoSQL Document Databases, Q3 2014.” In the report, Forrester cites MongoDB as a leader within the NoSQL Document Database category.
The database industry is undergoing tremendous change as new vendors emerge to address requirements around high volumes of semi-structured data. NoSQL enables businesses to leverage that data for next-generation applications.
As NoSQL gains momentum, business leaders need independent research to help understand the evolving database landscape. Forrester evaluated select vendors across a variety of criteria, including performance, scalability, high availability and other functionality. The complete analysis provides details on vendors’ business and technology, with assessments of development, operations, product roadmap, and more.
Read the full report to gain deeper insights into NoSQL document databases, including MongoDB.
Part 1: Your App is Taking Off, Now What? Understanding MongoDB Deployment Health.
Your app is on the front page of the app store. Hooray! Your service is suddenly flooded with new users and you have a problem that everyone envies: maintaining high performance while your app is under heavy load. Here’s what you need to think about to ensure deployment health. 1. Design Your Schema for Scale You may be surprised that the design of your schema will be a critical component of ensuring performance as your app grows. Your schema should be informed by your application’s use case and query patterns. A good schema will support your common app queries and updates, as well as allow you to create efficient indexes. In contrast, a poor schema can lead to storage fragmentation, make it difficult to efficiently query data and challenging to create indexes. Our rules of thumb blog post is a great resource when modeling your data, as is our Schema Design consultation package . 2. Optimize Your Indexes Many MongoDB users get great performance from a single replica set. Before throwing money at more expensive hardware or diving into sharding, make sure that you’ve got the right indexes in place and that you’ve tuned your queries. Our upcoming webinar on indexing strategies for scale will provide you with lots of useful tips and tricks on this topic. 3. Get the Right Hardware Does your working set fit in RAM? Are you relying on SSDs or HDDs? Are you prioritizing faster CPUs over more cores? Is your storage local or remote? Are you virtualizing or running on bare metal? The right hardware will optimize performance, while the wrong hardware can lead to problems down the line. This presentation on Hardware Provisioning from MongoDB World provides excellent advice using several real-world examples. 4. Look Inside with Monitoring Without visibility into your system, you can’t discover and diagnose issues. To optimize performance properly, first you need to identify what is actually slow! Using the monitoring functionality in MongoDB Management Service along with tools like mtools , mongostat and mongotop , you can visualize performance and identify bottlenecks. Taking it a step further, you can set up alerts in MMS to proactively inform you when key metrics are out of range. 5. Talk to an Expert You’re not the first to face these challenges. Thousands of organizations have built high performance, scalable applications on MongoDB. And we’ve helped most of them. So if you’re worried about performance and scalability, talk to an expert at MongoDB -- at no cost to you. In our next blog post, we’ll explore methods for scaling out MongoDB.
Solving Business Problems and Impacting Customer Experience with MongoDB’s Data Analytics Team
Chris Douglas is currently a Product Analytics Manager on MongoDB’s Data Analytics team in New York City. In this article, we discuss the team culture and growth, how analysts make an impact, and the close partnership they’ve built with our product organization. Read on to learn more about data analytics at MongoDB. Jackie Denner: Hi Chris! Thanks for sharing a bit about your experience on the Data Analytics team. Can you start off by telling me why you decided to join MongoDB? Chris Douglas: Coming from an SQL background, I hadn’t used MongoDB in my day-to-day but heard good things about it from developers. During the interview process, I quickly saw how passionate people were about the product and could clearly see how many interesting analytical challenges there were to solve. I joined as one of the first product analysts and have been at the company for about two and a half years. JD: It must have been exciting to be one of the first product analysts. How have you seen the Data Analytics team grow in that time? CD: The analytics team had about 14 people when I joined and has roughly tripled in size. What I’m most proud of is seeing how the team has grown with respect to maturity, complexity, and depth of work. We’ve invested a lot in telemetry to better understand where developers are in their journey and help them get the most out of MongoDB. Our growth and maturity has allowed us to help more teams across MongoDB make better data-driven decisions. JD: How do you feel you’ve personally grown since joining MongoDB? CD: Being surrounded by extremely driven and talented people has helped me learn as a person and helped me better understand how analytics can play a part in the software development cycle. The culture here really encourages collaboration, so I have the pleasure of working with a lot of different functions (from sales to marketing to product), which helps me holistically understand the MongoDB Atlas business. It’s been great to be surrounded by people with such diverse backgrounds and disciplines, and it has opened up my world view substantially. As the Data Analytics team has scaled, I’ve had the fortune of transitioning into a people manager role. This has been a great (but humbling) learning experience where I get to collaborate and work closely with two fantastic analysts. JD: Some of MongoDB’s core values are “Build Together,” “Make It Matter,” and “Own What You Do.” How does the analytics team experience these on a daily basis? CD: Our team vision is to empower a data-driven culture at MongoDB, which connects really well to our company values. We’re often the quantitative arm of any initiative or product starting from ideation all the way through retrospectives and measuring results. We collaborate with product managers to understand where there’s opportunity for growth, ideate experimentation with the design teams, and work with product marketing around target groups for outreach campaigns. Bringing a quantitative lens into the fold helps the team prioritize and learn as much as we can to create value for our customers. JD: It sounds like your team is a true partner to the product organization. How do you weave data and experimentation into the product roadmap? CD: The Data Analytics team is really here to help contextualize who is using products today and where there is opportunity to help solve pain points for developers. While nothing can replace qualitative user research, it’s nearly impossible to do this with everyone given our scale and growth. Experimentation is a great mechanism for us to learn and see what solutions work best for our customer base. A/B testing has let us learn so much, which helps us improve the customer experience and increase our pace of innovation. JD: What makes working in analytics at MongoDB exciting, and why should someone join the team? CD: MongoDB has the perfect mix of a startup culture with the advantages of working for a larger company. I could be chatting about the health metrics for MongoDB Atlas, then jump into a go-to-market strategy meeting for MongoDB Search, then talk to an economist about causal inference study strategies. There’s always something new. There’s a lot of trust and empowerment here that fosters a very collaborative and creative environment. This is largely because we’re tackling big challenges that can make a real impact for people using our product every day. The opportunity to take part in shaping the future roadmap of MongoDB products as well as knowing your work is making an impact is what excites me. Interested in making an impact as part of our Data Analytics team? View our open career opportunities — we’d love to help you transform your career at MongoDB.