We update MongoDB Cloud Manager regularly so that we can make it better for our customers. The latest version of Cloud Manager that was released on 2/22/16 introduced some significant changes and improvements. Continue reading below to learn more about the changes:
- Release of optimized navigation structure UI, including simplified Servers & Processes view. Take a look at the new Deployment tab to see the re-styled Servers and Processes tabs.
- Completely retooled user and roles management, giving users more flexibility over what is managed and what is not managed. You can find the users and roles under the “More” menu on the Deployment tab.
- Ability to convert a replica set to a sharded cluster
If you have any feedback, feel free to send us an e-mail at firstname.lastname@example.org. Thanks for using Cloud Manager!
Derivitec’s Risk Analysis Platform Uses MongoDB to Give Any Trader Access to Big-Bank Computing Power
Understanding future risk is vital for every successful organisation. In the financial markets, gaining that understanding means processing a mountain of complex data. In previous generations that meant you needed big computers and proprietary software that only big banks could afford. Thanks to better open source software and commodity hardware, that is no longer the case. Derivitec uses powerful modern infrastructure like MongoDB and AWS to make it possible for traders to get streamlined, industry standard financial analytics in minutes, not months. This gives them an understanding of what a range of different future events could mean for their investments. Answering the vital questions: What could go wrong? What’s the worst-case scenario? How can I hedge that risk? To address these questions Derivitec needed to build a different, more modern, platform. In 2011, when the company started, the team knew it would be processing a large volume and wide variety of data. So the database layer was going to be a defining factor for success. For the core functionality of the platform something fast, reliable and, above all, flexible was needed. New data sources, constantly changing regulations, and variable customer requirements meant functionality would be continually evolving. For Derivitec the obvious answer was a non-relational database with a document-oriented data model . Then, as now, MongoDB was a good fit. It’s worth pointing out that other no-SQL solutions were evaluated for this functionality but, quite simply, the performance levels were nowhere near what was needed. There are dozens of non-relational databases, but the choice was still a simple one. The three reasons for deciding on MongoDB were: Tried and tested technology – it has all the modern functionality and performance but it’s also got a massive community, thousands of customers and a mature support network. Operational tooling – Cloud Manager provides monitoring, backup and automation of deployments from the beginning - reducing costs and eliminating risk Ease of use – If you’re building a platform that will be easy to use, it makes sense to use one that’s easy to use too. MongoDB was also proven to run efficiently in the cloud, which is a huge part of what makes Derivitec special. In the early days Derivitec used Microsoft’s Azure cloud, but as its usage of MongoDB increased, the decision was made to switch from Azure to Amazon Web Services . Azure’s cloud was still too focused on its own software and it wasn’t as simple as it should have been to use non-Microsoft software, whilst AWS proved to be more accommodating. With that underlying infrastructure in place the platform could now be scaled out. MongoDB’s flexibility enabled Derivitec to deliver a system that could have users calculating risk on their portfolios in minutes, compared to the months it would have normally taken. For example, you can simply drop your trades in from Excel, visualise them, rearrange your portfolios, set up new portfolios, and manage the whole booking cycle natively within the app. The playing field is far from level. A big financial institution can still call a Napoleon's army of resources - both personnel and technology. But with the right data, enough context and access to intuitive tools you might just be able to see what your multiple futures hold. It’s exciting to be working in a time that modern open source software architectures and the power of cloud computing is eliminating obstacles and liberating giant ideas from giant budgets. About Derivitec Derivitec Ltd is a privately owned, UK based independent software vendor specialising in high performance, cost effective analytics for the derivatives industry. Founded in Dec 2011, the company have been working intensively towards cloud based solutions for risk and portfolio management. The Derivitec Risk Portal has been designed to allow users to start analysing risk on their derivatives portfolios in a matter of minutes. With industrial standard models and sanitised market data as standard, customers can focus on the business of business, while Derivitec concentrates on the business of risk. For an overview of MongoDB and its implementation on the AWS cloud platform read our guide. MongoDB on AWS: Guidelines and Best Practices About the Author - George Kaye George is the CEO and founder of Derivitec.
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.