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 .
How DataSwitch And MongoDB Atlas Can Help Modernize Your Legacy Workloads
Data modernization is here to stay, and DataSwitch and MongoDB are leading the way forward. Research strongly indicates that the future of the Database Management System (DBMS) market is in the cloud, and the ideal way to shift from an outdated, legacy DBMS to a modern, cloud-friendly data warehouse is through data modernization. There are a few key factors driving this shift. Increasingly, companies need to store and manage unstructured data in a cloud-enabled system, as opposed to a legacy DBMS which is only designed for structured data. Moreover, the amount of data generated by a business is increasing at a rate of 55% to 65% every year and the majority of it is unstructured. A modernized database that can improve data quality and availability provides tremendous benefits in performance, scalability, and cost optimization. It also provides a foundation for improving business value through informed decision-making. Additionally, cloud-enabled databases support greater agility so you can upgrade current applications and build new ones faster to meet customer demand. Gartner predicts that by 2022, 75% of all databases will be on the cloud – either by direct deployment or through data migration and modernization. But research shows that over 40% of migration projects fail. This is due to challenges such as: Inadequate knowledge of legacy applications and their data design Complexity of code and design from different legacy applications Lack of automation tools for transforming from legacy data processing to cloud-friendly data and processes It is essential to harness a strategic approach and choose the right partner for your data modernization journey. We’re here to help you do just that. Why MongoDB? MongoDB is built for modern application developers and for the cloud era. As a general purpose, document-based, distributed database, it facilitates high productivity and can handle huge volumes of data. The document database stores data in JSON-like documents and is built on a scale-out architecture that is optimal for any kind of developer who builds scalable applications through agile methodologies. Ultimately, MongoDB fosters business agility, scalability and innovation. Key MongoDB advantages include: Rich JSON Documents Powerful query language Multi-cloud data distribution Security of sensitive data Quick storage and retrieval of data Capacity for huge volumes of data and traffic Design supports greater developer productivity Extremely reliable for mission-critical workloads Architected for optimal performance and efficiency Key advantages of MongoDB Atlas , MongoDB’s hosted database as a service, include: Multi-cloud data distribution Secure for sensitive data Designed for developer productivity Reliable for mission critical workloads Built for optimal performance Managed for operational efficiency To be clear, JSON documents are the most productive way to work with data as they support nested objects and arrays as values. They also support schemas that are flexible and dynamic. MongoDB’s powerful query language enables sorting and filtering of any field, regardless of how nested it is in a document. Moreover, it provides support for aggregations as well as modern use cases including graph search, geo-based search and text search. Queries are in JSON and are easy to compose. MongoDB provides support for joins in queries. MongoDB supports two types of relationships with the ability to reference and embed. It has all the power of a relational database and much, much more. Companies of all sizes can use MongoDB as it successfully operates on a large and mature platform ecosystem. Developers enjoy a great user experience with the ability to provision MongoDB Atlas clusters and commence coding instantly. A global community of developers and consultants makes it easy to get the help you need, if and when you need it. In addition, MongoDB supports all major languages and provides enterprise-grade support. Why DataSwitch as a partner for MongoDB? Automated schema re-design, data migration & code conversion DataSwitch is a trusted partner for cost-effective, accelerated solutions for digital data transformation, migration and modernization through a modern database platform. Our no-code and low-code solutions along with cloud data expertise and unique, automated schema generation accelerates time to market. We provide end-to-end data, schema and process migration with automated replatforming and refactoring, thereby delivering: 50% faster time to market 60% reduction in total cost of delivery Assured quality with built-in best practices, guidelines and accuracy Data modernization: How “DataSwitch Migrate” helps you migrate from RDBMS to MongoDB DataSwitch Migrate (“DS Migrate”) is a no-code and low-code toolkit that leverages advanced automation to provide intuitive, predictive and self-serviceable schema redesign from a traditional RDBMS model to MongoDB’s Document Model with built-in best practices. Based on data volume, performance, and criticality, DS Migrate automatically recommends the appropriate ETTL (Extract, Transfer, Transform & Load) data migration process. DataSwitch delivers data engineering solutions and transformations in half the timeframe of the existing typical data modernization solutions. Consider these key areas: Schema redesign – construct a new framework for data management. DS Migrate provides automated data migration and transformation based on your redesigned schema, as well as no-touch code conversion from legacy data scripts to MongoDB Atlas APIs. Users can simply drag and drop the schema for redesign and the platform converts it to a document-based JSON structure by applying MongoDB modeling best practices. The platform then automatically migrates data to the new, re-designed JSON structure. It also converts the legacy database script for MongoDB. This automated, user-friendly data migration is faster than anything you’ve ever seen. Here’s a look at how the schema designer works. Refactoring – change the data structure to match the new schema. DS Migrate handles this through auto code generation for migrating the data. This is far beyond a mere lift and shift. DataSwitch takes care of refactoring and replatforming (moving from the legacy platform to MongoDB) automatically. It is a game-changing unique capability to perform all these tasks within a single platform. Security – mask and tokenize data while moving the data from on-premise to the cloud. As the data is moving to a potentially public cloud, you must keep it secure. DataSwitch’s tool has the capability to configure and apply security measures automatically while migrating the data. Data Quality – ensure that data is clean, complete, trustworthy, consistent. DataSwitch allows you to configure your own quality rules and automatically apply them during data migration. In summary: first, the DataSwitch tool automatically extracts the data from an existing database, like Oracle. It then exports the data and stores it locally before zipping and transferring it to the cloud. Next, DataSwitch transforms the data by altering the data structure to match the re-designed schema, and applying data security measures during the transform step. Lastly, DS Migrate loads the data and processes it into MongoDB in its entirety. Process Conversion Process conversion, where scripts and process logic are migrated from legacy DBMS to a modern DBMS, is made easier thanks to a high degree of automation. Minimal coding and manual intervention are required and the journey is accelerated. It involves: DML – Data Manipulation Language CRUD – typical application functionality (Create, Read, Update & Delete) Converting to the equivalent of MongoDB Atlas API Degree of automation DataSwitch provides during Migration Schema Migration Activities DS Automation Capabilities Application Data Usage Analysis 70% 3NF to NoSQL Schema Recommendation 60% Schema Re-Design Self Services 50% Predictive Data Mapping 60% Process Migration Activities DS Automation Capabilities CRUD based SQL conversion (Oracle, MySQL, SQLServer, Teradata, DB2) to MongoDB API 70% Data Migration Activities DS Automation Capabilities Migration Script Creation 90% Historical Data Migration 90% 2 Catch Load 90% DataSwitch Legacy Modernization as a Service (LMaas): Our consulting expertise combined with the DS Migrate tool allows us to harness the power of the cloud for data transformation of RDBMS legacy data systems to MongoDB. Our solution delivers legacy transformation in half the time frame through pay-per-usage. Key strengths include: ● Data Architecture Consulting ● Data Modernization Assessment and Migration Strategy ● Specialized Modernization Services DS Migrate Architecture Diagram Contact us to learn more.