Upcoming MongoDB Events
MongoDB will be featured at several events, conferences, and meetups in March, including a webinar on MongoDB internals, Mountain West Ruby Conference in Salt Lake City, NoSQL Live Boston, QCon London, and Cloud Connect in Santa Clara. There’s a MongoDB training session in San Francisco and there will even be a MongoDB Day in Austin! Check the Events page for a complete listing.
In addition, 10gen will be hosting MongoDB Office Hours on Wednesdays in New York City, starting on March 17. Stop by to meet the MongoDB team, ask questions, or have a beer.
MongoDB Office Hours
Wednesdays (Starting March 17)
4pm - 6pm
17 West 18th Street - 8th Floor
Between 5th & 6th Avenues
New York, NY
The best of the MongoDB presentations in February:
- MongoDB Isn’t Water - Kyle Banker at Chicago Ruby on February 2
- Introduction to MongoDB - Kristina Chodorow at FOSDEM (Brussels, Belgium) on February 7
- How Python, TurboGears, and MongoDB are Transforming SourceForge.net - Rick Copeland at PyCon (Atlanta, GA) on February 21
- Intro to MongoDB - Alex Sharp at LA WebDev Meetup on February 23
Announcing Speakers for NoSQL Live
It’s not too late to register for NoSQL Live in Boston on March 11 th . We have an exciting lineup of speakers and panelists who will discuss real use cases for NoSQL in production systems. Session topics at NoSQL Live will include scaling with NoSQL, NoSQL in the cloud, schema design with document-oriented databases, the evolution of graph data structure from research to production, the enterprise adoption of NoSQL, and toward web standards for NoSQL. In addition to speakers and panels, the conference will also include lightning talks and a NoSQL Lab for practical exploration of working with specific NoSQL products. Here’s the confirmed list of speakers, panelists, and moderators: – Dwight Merriman, CEO, 10gen – Eliot Horowitz, CTO, 10gen – Adam Kocoloski, CTO, Cloudant – Alan Hoffman, CEO, Cloudant – Durran Jordan, Senior Developer, Hashrocket – Les Hill, Software Adventurer, Hashrocket – Marko Rodriguez, Graph Systems Architect, AT&T Interactive – Ryan King, Technical Lead, Storage Team, Twitter – Alex Feinberg, Senior Software Engineer, LinkedIn – Jonathan Ellis, Systems Architect, The Rackspace Cloud – Sandro Hawke, Software Developer and Systems Architect, W3C – Benjamin Day, Microsoft MVP – Ryan Rawson, Systems Architect, StumbleUpon – Bryan Fink, Senior Software Developer, Basho Technologies – Rusty Klophaus, Senior Software Engineer, Basho Technologies – Adam Wiggins, Co-founder, Heroku – Mark Atwood, Director of Community Development, Gear6 – Sourav Mazumder, Principal Technology Architect, Infosys Technologies Limited – Tim Anglade, CTO, GemKitty – Bradford Stephens, Founder, Drawn to Scale – Doug Judd, CEO, Hypertable – Daniel Rinehart, Chief Software Architect, Allurent – Emil Eifrém, CEO, Neo Technology – Paul Davis, Research Assistant, New England Biolabs – Borislav Iordanov, Software Architecture Consultant, Kobrix – Jim Wilson, Lead Software Engineer, Vistaprint – Ryan Angilly, Senior Developer, Punchbowl Software Sign ups for the $40 early bird registration end today. If you’re interested in presenting or sponsoring, contact Meghan Gill, event coordinator, at firstname.lastname@example.org . Check out http://nosqlboston.eventbrite.com for more information and to register.
4 Critical Features for a Modern Payments System
The business systems of many traditional banks rely on solutions that are decades old. These systems, which are built on outdated, inflexible relational databases, prevent traditional banks from competing with industry disruptors and those already adopting more modern approaches. Such outdated systems are ill-equipped to handle one of the core offerings that customers expect from banks today — instantaneous, cashless, digital payments . The relational database management systems (RDBMSes) at the core of these applications require breaking data structures into a complex web of tables. Originally, this tabular approach was necessary to minimize memory and storage footprints. But as hardware has become cheaper and more powerful, these advantages have also become less relevant. Instead, the complexity of this model results in data management and programmatic access issues. In this article, we’ll look at how a document database can simplify complexity and provide the scalability, performance, and other features required in modern business applications. Document model To stay competitive, many financial institutions will need to update their foundational data architecture and introduce a data platform that enables a flexible, real-time, and enriched customer experience. Without this, new apps and other services won’t be able to deliver significant value to the business. A document model eliminates the need for an intricate web of related tables. Adding new data to a document is relatively easy and quick since it can be done without the usually lengthy reorganization that RDBMSes require. What makes a document database different from a relational database? Intuitive data model simplifies and accelerates development work. Flexible schema allows modification of fields at any time, without disruptive migrations. Expressive query language and rich indexing enhance query flexibility. Universal JSON standard lets you structure data to meet application requirements. Distributed approach improves resiliency and enables global scalability. With a document database, there is no need for complicated multi-level joins for business objects, such as a bill or even a complex financial derivative, which often require object-relational mapping with complex stored procedures. Such stored procedures, which are written in custom languages, not only increase the cognitive load on developers but also are fiendishly hard to test. Missing automated tests present a major impediment to the adoption of agile software development methods. Required features Let’s look at four critical features that modern applications require for a successful overhaul of payment systems and how MongoDB can help address those needs. 1. Scalability Modern applications must operate at scales that were unthinkable just a few years ago, in relation to both transaction volume and to the number of development and test environments needed to support rapid development. Evolving consumer trends have also put higher demands on payment systems. Not only has the number of transactions increased, but the responsive experiences that customers expect have increased the query load, and data volumes are growing super-linear. The fully transactional RDBMS model is ill suited to support this level of performance and scale. Consequently, most organizations have created a plethora of caching layers, data warehouses, and aggregation and consolidation layers that create complexity, consume valuable developer time and cognitive load, and increase costs. To work efficiently, developers also need to be able to quickly create and tear down development and test environments, and this is only possible by leveraging the cloud. Traditional RDBMSes, however, are ill suited for cloud deployment. They are very sensitive to network latency, as business objects spread across multiple tables can only be retrieved through multiple sequential queries. MongoDB provides the scalability and performance that modern applications require. MongoDB’s developer data platform also ensures that the same data is available for use with other frequent consumption patterns like time series and full-text search . Thus, there is no need for custom replication code between the operational and analytical datastore. 2. Resiliency Many existing payment platforms were designed and architected when networking was expensive and slow. They depend on high-quality hardware with low redundancy for resilience. Not only is this approach very expensive, but the resiliency of a distributed system can never be reached through redundancy. At the core of MongoDB’s developer data platform is MongoDB Atlas , the most advanced cloud database service on the market. MongoDB Atlas can run in any cloud, or even across multiple clouds, and offers 99.995% uptime. This downtime is far less than typically expected to apply necessary security updates to a monolithic legacy database system. 3. Locality and global coverage Modern computing demands are at once ubiquitous and highly localized. Customers expect to be able to view their cash balances wherever they are, but client secrecy and data availability rules set strict guardrails on where data can be hosted and processed. The combination of geo-sharding, replication, and edge data addresses these problems. MongoDB Atlas in combination with MongoDB for Mobile brings these powerful tools to the developer. During the global pandemic, more consumers than ever have begun using their smartphones as payment terminals. To enable these rich functions, data must be held at the edge. Developing the synchronization of the data is difficult, however, and not a differentiator for financial institutions. MongoDB for Mobile, in addition with MongoDB’s geo-sharding capability on Atlas cloud, offloads this complexity from the developer. 4. Diverse workloads and workload isolation As more services and opportunities are developed, the demand to use the same data for multiple purposes is growing. Although legacy systems are well suited to support functions such as double entry accounting, when the same information has to be served up to a customer portal, the central credit engine, or an AI/ML algorithm, the limits of the relational databases become obvious. These limitations have resulted in developers following what is often called “best-of-breed” practices. Under this approach, data is replicated from the transactional core to a secondary, read-only datastore based on technology that is better suited to the particular workload. Typical examples are transactional data stores being copied nightly into data lakes to be available for AI/ML modelers. The additional hardware and licensing cost for this replication are not prohibitive, but the complexity of the replication, synchronization, and the complicated semantics introduced by batch dumps slows down development and increases both development and maintenance costs. Often, three or more different technologies are necessary to facilitate the usage patterns. With its developer data platform, MongoDB has integrated this replication, eliminating all the complexity for the developers. When a document is updated in the transactional datastore, MongoDB will automatically make it available for full-text search and time series analytics. The pace of change in the payments industry shows no signs of slowing. To stay competitive, it’s vital that you reassess your technology architecture. MongoDB Atlas is emerging as the technology of choice for many financial services firms that want to free their data, empower developers, and embrace disruption. Replacing legacy relational databases with a modern document database is a key step toward enhancing agility, controlling costs, better addressing consumer expectations, and achieving compliance with new regulations. Learn more by downloading our white paper “Modernize Your Payment Systems."