MMS offers point-in-time recovery for replica sets and consistent snapshots for sharded systems. It is also one of the lowest overhead ways to backup MongoDB, continually reading the oplog and transferring the data encrypted to the backup service.
The free tier will be available to new users during their first 12 months using MMS Backup. In that period, any monthly bill under $5 is free. What does $5 get you? It’s roughly enough to back up a 2GB database with 500MB of oplog data churn per month.
With the free tier in place, we expect MongoDB users to take advantage of this offering in a variety of ways. The free tier can be used to sample the service for a larger, mission critical application. You can also leverage MMS during development before your dataset grows. And the free tier is perfect for side projects that you want to safeguard but don’t have the time to invest in building a backup strategy.
Getting started with MMS Backup is easy:
- Create an account at mms.mongodb.com
- Install monitoring on your deployment (monitoring is free)
- Go to the Backup tab to accept legal terms and enter credit card details
- Install an agent in your environment and start an initial sync to our datacenters
- Rest assured knowing that your backups are reliable and safe
MongoDB's $150 Million Funding Round: It's about the Customer Experience
Today MongoDB announced that we raised $150 million from a variety of investors both new (Salesforce.com, T.Rowe Price, EMC and others) and old (Sequoia, Red Hat, NEA, Flybridge, etc.). It's a great day for MongoDB, both the company and the project. But mostly it's a great day for our customers and the MongoDB community in which they participate. Hip With The Hackers Over the last few years MongoDB has solidified its position as the industry's leading NoSQL database and the fastest-growing Big Data community . With this funding round, MongoDB is also the best funded Big Data technology. As enterprises invest in Big Data, they turn to the two dominant Big Data technologies, MongoDB and Hadoop , as Wikibon analysis has shown. Importantly, as can be seen in an analysis of LinkedIn profiles by 451 Research, very often enterprises discover that they already have MongoDB expertise within their organizations: Much of this success derives from MongoDB giving developers a better way to create applications . Rather than commoditizing a legacy relational database (RDBMS) market, similar to what other open-source RDBMSs have done, MongoDB significantly increases developer productivity by offering them a flexible data model. MongoDB is a significant part of what Cowen & Co. analyst Peter Goldmacher calls a "fundamental shift in the technology landscape away from legacy systems towards a new breed of better products at a lower cost for Data Management, Apps and in other areas." In other words, MongoDB is empowering the next generation of applications: post-transactional applications that rely on bigger data sets that move much faster than an RDBMS can handle. Developers have responded, voting with their apps, a considerable number of which are backed by MongoDB. A Means, Not An End Given the opportunity ahead of us, MongoDB would be irresponsible to raise less. While most of our funding comes from rapidly growing revenues, the MongoDB board of directors determined that it would be advantageous to the project and, hence, to our customers, to accelerate growth. After all, our relational database competitors have a 30-year headstart. As Max Schireson, MongoDB's CEO, articulated on his blog: We are in a market dominated by technologies with over 30 years of engineering in them. Their designs may not be as well suited to modern applications, but they are very mature, very feature rich, and have huge partner ecosystems and big companies that understand the needs of their enterprise customers behind them. They have way more tooling – and decades of refinement of operational tools. This is why we are raising $150 million. We know that it will take a large and sustained effort to build the maturity that many users expect in this market. Building out our management suite and enhancing the core product will be a ton of work. We have made great progress on security, management, stability, and scalability but we still have so much to do. For next-generation workloads in the cloud, MongoDB is already taking a lead, as Amazon Web Services data from Stackdriver seems to suggest: But MongoDB isn't intended to be a cloud-only database. It's a general purpose database, designed to be a great fit for the vast majority of worklads. We want to make it easy to run on a single node or at massive scale in the cloud or on premise. Whatever the customer needs. This funding will help. Helping Ops Fall In Love With MongoDB Some of that work will be done by MongoDB's exceptional community of developers and business partners. Among other things, the MongoDB community has contributed over 20 drivers, tripling the language compatibility of MongoDB and making it much more approachable for developers, whatever their preferred programming language. But some of it will necessarily be done by MongoDB, Inc. From Linux to JBoss to Drupal, much of the best tooling has had to be developed by a focused, highly incentivized company. MongoDB is no different. We believe we have built the world's best database for developers. Now we need to make sure it is also the world's best database for Operations professionals. So that means an improved and expanded management suite. We recently added Backup , but there are other areas that will help Operations professionals more easily manage MongoDB at the scale that we increasingly see enterprises run the database. Outside of tooling, we also recognize that we need to continue to make improvements to MongoDB's concurrency, further optimize performance and more. We don't by any stretch think we're done. The Path Forward But we're making excellent progress. In the last year since I joined MongoDB I've seen the company double its headcount and dramatically expand sales. This funding not only lets us make significant investments in improving MongoDB for both developers and Operations, but it also helps us to fund expansion geographically. We're already growing 300% or more in Europe year-over-year, and expect much of the same in Asia-Pacific. We need to help support our customers wherever they may be. Given the historic opportunity before MongoDB, it's time to step on the accelerator. Hard. -- If you're interested, please find more coverage of the funding at BusinessWeek , GigaOm , TechCrunch , VentureBeat , and ZDNet .
MACH Aligned for Retail (Microservices, API-First, Cloud Native SaaS, Headless)
Across the Retail industry, MACH principles and the Mach Alliance are becoming increasingly common. What is MACH and why is it being embraced for Retail? The MACH Alliance is a non-profit organization fostering the adoption of composable architecture principles. It stands for Microservices, API-First, Cloud-Native SaaS and Headless. The MACH Alliance’s Manifesto is to: “Future proof enterprise technology and propel current and future digital experiences" The MACH Alliance and the creation of this set of principles originated in the Retail Industry. Several of the 5 co-founders of the MACH Alliance are technology companies building for retail use cases: for example commercetools is a composable commerce platform for retail (built completely on MongoDB). MongoDB has been a member of the MACH Alliance since 2020, as an “enabler” member, meaning use of our technology can enable the implementation of the MACH principles in application architectures. This is because a data layer built on MongoDB is ideal as the basis for a MACH architecture. Members of our Industry Solutions team sit on the MACH technology, growth and marketing councils, and actively are involved with furthering the adoption of MACH across the Retail Industry What is MACH, why is it important for retail? The retail industry has long been a fast adopter of technology and a forerunner in technology trends. This is because of the competitive nature of the business leading a drive towards innovation- its vital that retails are able to react quickly to new technologies (e.g. NFTs, VR, AI) to capture market share and stay ahead of the competitors. Retailers have realized that to be able to deliver new and value-add experiences to their customers, they have to cut back on operational overhead that leads to increased cost and build standard functionality that can either be bought or re-used. This is where the benefits of MACH comes in- it's all about increasing the ability to deliver innovation quickly while lowering operational costs & risk. Microservices: An approach to building applications in which business functions are broken down into smaller, self-contained components called services. These services function autonomously and are usually developed and deployed independently. This means the failure or outage of one microservice will not affect another and teams can develop in parallel, increasing efficiency. API-First: A style of development where the sharing and use of the data via API (application programming interface) is considered first and foremost in the development process. This means that services are designed to aid the easy sharing of information across the organization and simple interconnectivity of systems. Cloud-Native SaaS: Cloud-native SaaS solutions are vendor-managed applications developed in and for the cloud, and leveraging all the capabilities the cloud has to offer, such as fully managed hosting, built-in security, auto-scaling, cross-regional deployment and automatic updates. These are a good fit for a MACH architecture as adopting them can reduce operational costs and frees up developers for value-add work like new unique customer experiences. Headless: Decoupling the front end from the back-end so that front ends (or “heads”) can be created or iterated on with no dependencies on the back end. The fact that the layers are loosely coupled decreases time to market for new front ends, and encourages the re-use back-end services for multiple purposes. It also de-risks change in the long term as services can function independently. Where does MongoDB come in? MongoDB is an enabler for MACH, meaning that using MongoDB as your data layer helps retailers and retail software companies. achieve MACH compliance. Our data model, architecture and functionality empower IT organizations to build in line with these architecture principles. During a digital transformation, where a retailer is modernizing a monolith into a microservices based architecture, they're looking for a data layer which will enable speed of development & change. MongoDB is the "most wanted" database 4 years running on Stack Overflow's developer survey- this is because our document model maps to the way developers are thinking & coding, and the flexibility allows for iterative change of the data layer. When looking at API based communication, the standard format for APIs is JSON, which again maps to MongoDB's document model. The idea with API-first development is to develop with the API in mind- why not store the data the way you're going to serve it by API. This reduces complexity and increases performance. Cloud Native and SaaS products have become the norm as retailers wish to reduce maintenance and management work. MongoDB Atlas, provides a database-as-a-service, guaranteeing 99.995% uptime, automatic failover and self-healing and allowing DevOps engineers to spin up databases in minutes or by API/ script. Many retail software companies are also built on MongoDB Atlas- for example commercetools, which provides an ecommerce solution as a SaaS product. Headless architectures require a data layer that is able to adapt and change for new workloads. The ability to change the schema at runtime, with no downtime, makes MongoDB's document model ideal for this. Performance and the ability to scale for new "heads" is also important. MongoDB is known as a high performance database and can scale vertically automatically or scale out horizontally seamlessly. So MongoDB becomes a great choice for retailers choosing to adopt a MACH architecture (see figure 1 below). As a general purpose database with high performance, a rich expressive query language and secondary indexing, MongoDB is a really good fit as a data layer as it is capable of handling operational and analytical needs of the application. FIgure 1: Example of a MACH architecture Want to know more? Are you interested in a transition to MACH? Dive into our four part blog series exploring each topic in detail and how MongoDB supports each of these principles: Microservices API-First Cloud-Native SaaS Headless