In February, we announced that MongoDB 4.0 will support multi-document transactions. Curious to know what this will look like? Aly Cabral, Product Manager at MongoDB, is excited to share an early version of the syntax:
Each feature we build is with users like you in mind. When you attend our events, you’re able to connect with the people who work on the database you use every day – like Aly. In sessions, Birds of a Feather meetings, and one-on-one in Ask the Experts, you get to ask questions, share ideas, and be heard.
Additionally, you learn tips and tricks from power users and companies that will allow you to optimize your deployments. To get your hands on new tools to accelerate your development goals, join us at MongoDB World, June 26-27 in NYC.
Early Bird pricing ends Friday, May 11. Tickets are going fast! Sign up now to get your discounted conference pass. Don't forget, groups automatically get 25% off!
Date: June 26-27, 2018
Location: New York Hilton Midtown, 1335 6th Ave, New York, NY 10019
Learn More & Sign Up: mongodbworld.com
DarwinBox Evolves HR SaaS Platform and Prepares for 10x Growth with MongoDB Atlas
DarwinBox found a receptive market for its HR SaaS platform for medium to large businesses, but rapid success strained their infrastructure and challenged their resources. We talked to Chaitanya Peddi, Co-founder and Head of Product to find out how they addressed those challenges with MongoDB Atlas . Evolution favors those that find ways to thrive in changing environments. DarwinBox has done just that, providing a full spectrum of HR services online and going from a standing start to a top-four sector brand in the Indian market in just two years. From 40 enterprise clients in its first year to more than 80 in its second, it now supports over 200,000 employees, and is hungrily eyeing expansion in new territories. “We’re expecting 10x growth in the next two years,” says Peddi. “That means aggressive scaling for our platform and MongoDB Atlas will play a big role." Starting from a blank sheet of paper The company’s key business insight is that employees have grown accustomed to the user experience of online services they access in their personal lives. However, the same ease of use is simply not found at work, especially in HR solutions that address holiday booking, managing benefits, and appraisals. DarwinBox’s approach is to deliver a unified platform of user-friendly HR services to replace a jumble of disparate offerings, and to do so in a way that supports its own aggressive growth plans. The company aims to support nearly every employee interaction with corporate HR, such as recruitment, employee engagement, expense management, separation, and more. “We started in 2015 from a blank sheet of paper,” Peddi says. “It became very clear very quickly that for most of our use cases, only a non-relational database would work. Not only did we want to provide an exceptionally broad set of integrated services, but we also had clients with a large number of customization requirements. This meant we needed a very flexible data model. We looked at a lot of options. We wanted an open source technology to avoid lock-in and our developers pushed for MongoDB, which fit all our requirements and was a pleasure to work with. Our databases are now 90 percent MongoDB. We expect that to be at 100 percent soon.” Reducing costs and future-proofing database management When DarwinBox launched, it ran its databases in-house, which wasn’t ideal. “We have a team of 40+ developers, QA and testers, and three running infrastructure, and suddenly we’re growing much faster than we expected. It’s a good problem to have, but we couldn’t afford to offer anything less than excellent service.” Peddi emphaszied that of all the things they wanted to do to succeed, becoming database management experts wasn’t high on the list. This wasn’t the only reason that MongoDB Atlas looked like the next logical step for the company when it became available, says Peddi, “We were rapidly developing our services and our customer base, but our strategies for backing up the databases, for scaling, for high availability, and for monitoring performance weren’t keeping up. In the end, we decided that we’d migrate to Atlas for a few major reasons.” The first reason was the most obvious. “The costs of managing the databases, infrastructure, and backups were increasing. In addition, it became increasingly difficult to self-manage everything as requirements became more sophisticated and change requests became more frequent. Scaling up and down to match demand and launching new clusters consumed precious man hours. Monitoring performance and issue resolution was taking up more time than we wanted. We had built custom scripts, but they weren’t really up to the task.” With MongoDB Atlas on AWS, Peddi says, all these issues are greatly reduced. “We’re able to do everything we need with our fully managed database very quickly – scale according to business need at the press of a button, for example. There are other benefits. With MongoDB technical engineers a phone call away, we’re able to fix issues far quicker than we could in the past. MongoDB Compass, the GUI for the database, is proving helpful in letting our teams visually explore our data and tune things accordingly.” Migrating to Atlas has also helped Darwinbox dramatically reduce costs. We’ve optimized our database infrastructure and how we manage backups. Not only did we bring down costs by 40%, but by leveraging the queryable snapshot feature, we’re able to restore the data we actually need 80% faster. Chaitanya Peddi, Co-founder and Head of Product, DarwinBox The increased availability and data resilience from the switch to MongoDB Atlas on AWS eases the responsibility in managing the details of 200,000 employees’ working lives. “Data is the most sensitive part of our business, the number one thing that we care about,” says Peddi, “We can’t lose even 0.00001 percent of our data. We used to take snapshots of the database, but that was costly and difficult to manage. Now, it’s more a live copy process. We can guarantee data retention for over a year, and it only takes a few moments to find what you need with MongoDB Atlas.” For DarwinBox to achieve its target of 10x growth in two years, it has to – and plans to – go international. “We had that in mind from the outset. We’ve designed our architecture to cope with a much larger scale, both in total employee numbers and client numbers, and to handle different regulatory regimes.” According to Peddi, that means moving to microservices, developing data analytics, maybe even looking at other cloud providers to host the DarwinBox HR Platform. He added: “If we were to do this on AWS and self-manage the database with our current resources, we would have to invest a significant amount of effort into orchestrating and maintaining a globally distributed database. MongoDB Atlas with its cross-region capabilities makes this all much easier.” Darwinbox is confident that MongoDB Atlas will help the organization achieve its product plans. “MongoDB Atlas will be able to support the business needs that we've planned out for the next two years.” says Peddi, “We’re happy to see how rapidly the Atlas product roadmap is evolving.” Get started with MongoDB Atlas and deploy a free database in minutes.
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.