On June 1-2, over 2,000 developers, sysadmins, and DBAs will converge in New York City for MongoDB World, our annual user conference. It’s your chance to to get inspired, share ideas and get the latest insights on using MongoDB.
If you’re active on social media, you may have a chance to win a free conference pass. Simply share your enthusiasm for MongoDB World on Twitter during the month of March.
How to Enter
- Follow @mongodb or @mongodbinc on Twitter
- Tell us why you’re excited about MongoDB World by tweeting with a mention of @mongodb or @mongodbinc and make sure to use the #MongoDBWorld hashtag. Get creative! Start conversations, use humor, share photos, tell us what speakers you look forward to hearing from.
Click to tweet: I can't wait for #MongoDBWorld w/ @MongoDB because...
## Prizes 1st Prize: Ticket to MongoDB World 2015 2nd Prize: Fully loaded MongoDB World swag pack 3rd Prize: MongoDB T-shirt
How Winners Will Be Selected
MongoDB will pick the winning applicant by April 3rd, and will notify the winner via twitter direct message. The winners will be chosen based on a combination of most widely shared content and creativity used to experience their excitement about MongoDB World.
Call for Feedback: The New PHP and HHVM Drivers
In the beginning Kristina created the MongoDB PHP driver. Now the PECL mongo extension was new and untested, write operations tended to be fire-and-forget, and Boolean parameters made more sense than $options arrays. And Kristina said, "Let there be MongoCollection," and there was basic functionality. Since the PHP driver first appeared on the scene, MongoDB has gone through many changes. Replica sets and sharding arrived early on, but things like the aggregation framework and command cursors were little more than a twinkle in Eliot's eye at the time. The early drivers were designed with many assumptions in mind: write operations and commands were very different; the largest replica set would have no more than a dozen nodes; cursors were only returned by basic queries. In 2015, we know that these assumptions no longer hold true. Beyond MongoDB's features, our ecosystem has also changed. When the PHP driver, a C extension, was first implemented, there wasn't yet a C driver that we could utilize. Therefore, the 1.x PHP driver contains its own BSON and connection management C libraries. HHVM , an alternative PHP runtime with its own C++ extension API, also did not exist years ago, nor was PHP 7.0 on the horizon. Lastly, methods of packaging and distributing libraries have changed. Composer has superseded PEAR as the de facto standard for PHP libaries and support for extensions (currently handled by PECL) is forthcoming. During the spring of 2014, we worked with a team of students from Facebook's Open Academy program to prototype an HHVM driver modeled after the 1.x API. The purpose of that project was twofold: research HHVM's extension API and determine the feasibility of building a driver atop libmongoc (our then new C driver) and libbson . Although the final result was not feature complete, the project was a valuable learning experience. The C driver proved quite up to the task, and HNI, which allows an HHVM extension to be written with a combination of PHP and C++, highlighted critical areas of the driver for which we'd want to use C. This all leads up to the question of how best to support PHP 5.x, HHVM, and PHP 7.0 with our next-generation driver. Maintaining three disparate, monolithic extensions is not sustainable. We also cannot eschew the extension layer for a pure PHP library, like mongofill , without sacrificing performance. Thankfully, we can compromise! Here is a look at the architecture for our next-generation PHP driver: At the top of this stack sits a pure PHP library, which we will distribute as a Composer package. This library will provide an API similar to what users have come to expect from the 1.x driver (e.g. CRUD methods, database and collection objects, command helpers) and we expect it to be a common dependency for most applications built with MongoDB. This library will also implement common specifications , in the interest of improving API consistency across all of the drivers maintained by MongoDB (and hopefully some community drivers, too). Sitting below that library we have the lower level drivers (one per platform). These extensions will effectively form the glue between PHP and HHVM and our system libraries (libmongoc and libbson). These extensions will expose an identical public API for the most essential and performance-sensitive functionality: Connection management BSON encoding and decoding Object document serialization (to support ODM libraries) Executing commands and write operations Handling queries and cursors By decoupling the driver internals and a high-level API into extensions and PHP libraries, respectively, we hope to reduce our maintainence burden and allow for faster iteration on new features. As a welcome side effect, this also makes it easier for anyone to contribute to the driver. Additionally, an identical public API for these extensions will make it that much easier to port an application across PHP runtimes, whether the application uses the low-level driver directly or a higher-level PHP library. GridFS is a great example of why we chose this direction. Although we implemented GridFS in C for our 1.x driver, it is actually quite a high-level specification. Its API is just an abstraction for accessing two collections: files (i.e. metadata) and chunks (i.e. blocks of data). Likewise, all of the syntactic sugar found in the 1.x driver, such as processing uploaded files or exposing GridFS files as PHP streams, can be implemented in pure PHP. Provided we have performant methods for reading from and writing to GridFS' collections – and thanks to our low level extensions, we will – shifting this API to PHP is win-win. Earlier I mentioned that we expect the PHP library to be a common dependency for most applications, but not all. Some users may prefer to stick to the no-frills API offered by the extensions, or create their own high-level abstraction (akin to Doctrine MongoDB for the 1.x driver), and that's great! Hannes has talked about creating a PHP library geared for MongoDB administration, which provides an API for various user management and ops commands. I'm looking forward to building the next major version of Doctrine MongoDB ODM directly atop the extensions. While we will continue to maintain and support the 1.x driver and its users for the foreseeable future, we invite everyone to check out our next-generation driver and consider it for any new projects going forward. You can find all of the essential components across GitHub and JIRA: Project GitHub JIRA PHP Library mongodb/mongo-php-library PHPLIB PHP 5.x Driver (phongo) mongodb/mongo-php-driver PHPC HHVM Driver (hippo) mongodb/mongo-hhvm-driver HHVM The existing PHP project in JIRA will remain open for reporting bugs against the 1.x driver, but we would ask that you use the new projects above for anything pertaining to our next-generation drivers. If you're interested in hearing more about our upcoming PHP and HHVM drivers, Derick Rethans is presenting a new talk entitled One Extension, Two Engines at php[tek] 2015 in May. About the Author - Jeremy Jeremy Mikola is a software engineer at MongoDB's NYC office. As a member of the driver and evangelism team, he helps develop the PHP driver and contributes to various OSS projects, such as Doctrine ODM and React PHP. Jeremy lives in Hoboken, NJ and is known to enjoy a good sandwich.
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.