This is a guest post by Eric Barroca, CEO - Nuxeo.
Digitizing content and processes is a 20- or even 30-year-old story. The first wave of solutions delivered huge efficiency gains for enterprises – from paper, to PDF and checks, to Paypal. Today, companies across industries – from Media to Financial Services to Telecommunications – see new opportunities in a second wave of technology, such as creating new revenue streams and developing new products and services for their customers. But, so many are still managing their content in systems architected in the first wave and which now stand in the way of transformation.
Legacy systems can't support today's digital transformation needs. They lack the enterprise-wide visibility, searchability and control to keep content and the metadata that makes it valuable together. They are staggering under the crush of complexity of content and firehose of information flowing in and out of these systems on a daily basis. And, after implementation, they can’t be easily adapted to today’s ever-more dynamic and unpredictable business needs and opportunities.
To succeed in your business transformation, you need an approach that can unlock the value of assets through a system that can see, search and manage assets and metadata across 100s or even 1,000s of places across your enterprise. You need to multiply the value of your assets by empowering your entire business to easily leverage these critical assets and information. You need to accelerate innovation by leveraging the speed and investment of a cloud services ecosystem. And, you have to assume and plan for evolution and scale as your business responds to new opportunity and growth.
Nuxeo & MongoDB Enterprise Advanced: Unmatched Performance in Content Management
Nuxeo’s integration with MongoDB Enterprise Advanced, as an alternative to a relational database, is first of its kind in the Enterprise Content Management (ECM) space. The Nuxeo Platform for content management and Digital Asset Management (DAM) allows enterprises to discover the full value of their most complex digital assets, and scales to support even the largest content repositories, leveraging MongoDB Enterprise Advanced’s scaling, performance and replication capabilities.
Legacy ECM systems fall short when trying to turn data into valuable assets. Content Management and Digital Asset Management are now data-centric. Digital assets are core to any successful digital transformation. Unfortunately, value is often locked in the data surrounding these assets and many organizations have trouble unlocking this data to enable true transformation. The Nuxeo Platform helps to transform this data into valuable assets and, together with MongoDB Enterprise Advanced, allows enterprises to do it at true enterprise scale.
High performance of the Nuxeo Platform has already been tested and benchmarked to the tune of several billion documents with MongoDB Enterprise Advanced. The latest benchmarks from Nuxeo on an average cloud instance and using complex content objects now show the following results:
- Document Processing: 30,000 doc/sec
- Bulk Import: 5x faster than any relational database implementation
- Overall, a 15x performance increase compared to the fastest relational database implementation
Check out our benchmark results and learn more in this video: Using MongoDB Enterprise Advanced to Build a Fast and Scalable Document Repository
Why MongoDB Enterprise Advanced as a backend storage for Nuxeo apps
Nuxeo chose MongoDB Enterprise Advanced because it enables organizations to deploy cloud-ready applications with unmatched performance and scalability. Used with the Nuxeo Platform, MongoDB Enterprise Advanced provides a database storage option offering high performance, high availability, and exceptional scalability for Enterprise Content Management (ECM) applications.
Nuxeo customers with extremely large content store requirements are able to leverage MongoDB Enterprise Advanced to get features such as replication, zero downtime and scalability. It is also a good combination with Elasticsearch, leveraging Elastic for advanced queries and MongoDB Enterprise Advanced for highly scalable content and asset storage. Nuxeo customers now have access to capabilities such as full-index support, rich querying, auto-sharding, replication and high availability, and much more.
Using the Nuxeo Platform with MongoDB Enterprise Advanced provides the opportunity to build content management applications with big data tools capable of dealing with complex, enterprise-scale data volumes at unmatched speeds.
Nuxeo for Giant ECM Applications
Nuxeo provides a Hyperscale Digital Asset Platform that helps enterprise organizations unlock the full value of their digital assets to create new revenue streams, improve performance, and maximize existing IT investments. Over 200 leading organizations use Nuxeo for digital asset management, document management, knowledge management, and other content-centric business applications.
Nuxeo is headquartered in New York with five additional offices worldwide, and raised $30 million in capital from Goldman Sachs and Kennet Partners in 2016.
More information is available at www.nuxeo.com.
The Modern Application Stack - Part 5: Using ReactJS, ES6 & JSX to Build a UI (the rise of MERN)
Engineering, Done DIRT Cheap: How an Outdated Data Architecture Becomes a Tax on Innovation
In March 2021, I wrote about The Innovation Tax : the idea that clunky processes and outdated technologies make it harder for engineering teams to produce excellent tech that delights customers. In the months since then, my thinking has evolved even further. I couldn’t have guessed how many technology leaders would immediately recognize these problems in their own organizations and share their own deep frustrations with me. This article puts that evolved thought together with the massive feedback that piece received. It will give you actionable ways to decrease your tax burden — and who wouldn’t want that? The innovation tax, like income tax, is real. Of course, it saps morale (with resulting attrition and churn), but it also has other financial and opportunity costs. Taxed organizations see their pace of innovation suffer as people and resources are locked into maintaining rather than innovating. We named this tax DIRT . Why? Well, it’s rooted in data (D), because it so often springs from the difficulty of using legacy databases to support modern applications that require access to real-time data to create rich user experiences. It affects innovation (I), because your teams have little time to innovate if they’re constantly trying to figure out how to support a complex and rickety architecture. It’s recurring (R), because it’s not as if you pay the tax (T) once and get it over with. Quite the opposite. DIRT makes each new project ever more difficult because it introduces so many components, frameworks, and protocols that need to be managed by different teams of people. In retrospect, it’s clear that technology leaders would recognize this tax and immediately grasp the degree to which it’s caused -- or cured -- by their data architecture. Data is sticky, strategic, heavy, intricate -- and the core of the modern digital company. Modern applications have much more sophisticated data requirements than the applications we were building only 10 years ago. Obviously, there is more data, but it’s more complicated than that: Companies are expected to react more quickly and more cleverly to all of the signals in that data. Legacy technologies, including single-model rigid, inefficient, and hard-to-program relational databases, just don’t cut it. In over 300 CxO conversations I've had since joining MongoDB in 2020, fewer than a handful of CTOs disputed this statement. When your tech stack can’t handle the demands of new applications, engineering teams will often bolt on single-purpose niche databases to do the job (think time series, text, graph, etc.). Then they’ll build a series of pipelines to move data back and forth. And everything will get slow and complicated — and even political. Time to polish up that LinkedIn profile. If this were rare, it wouldn’t be such a big deal. But large enterprises can have hundreds or thousands of applications, each with their own sources of data and their own pipelines. Over time, as data stores and pipelines multiply, an organization’s data architecture starts to look like a plate of spaghetti. Soon you’re operating and maintaining an entire middleware layer of ETL, ELT, and streaming. The variety of technologies, each with their own frameworks, protocols, and sometimes languages, makes it harder for developers to collaborate. It makes it extremely difficult to scale, because every architecture is bespoke and brittle. Developers spend their precious “flow” hours doing integration work instead of building new applications and features that the business needs and customers will love. Enterprise architects often end up spending their time on all the wrong things. It’s clear to me that most customers are ready for a new approach to data architecture. One of the best parts of my job is listening to and learning from other CxOs. Since the pandemic made it impossible to do that in person, MongoDB moved these discussions online, inviting technology leaders to hash out some of their biggest problems 1:1 and in groups with me. In one of those sessions, a CTO commented, “Technical debt should be carried on your CFO's balance sheet.” Even on Zoom, the power of that statement was clear. We also started looking at slide decks about data architecture from some of the best-known venture capital firms. Certainly VCs must position each of their portfolio companies as a critical player in the data architecture of the future. But the overall vision was not compelling. One technology leader said, “When I look at 20 net-new technologies I need to learn, it’s terrifying.” Others commented that just looking at these architecture diagrams was a little off-putting, because they knew their own organization’s data architecture was at least that complicated already. They knew they needed to simplify their data architecture, but more than one admitted to postponing this work -- indefinitely -- because it was just too daunting. I recently met with a major health care company whose executives think it’s just barely possible, but they are bravely diving in anyway, knowing that they must do it and that they’ll learn along the way as they tear down their monoliths. In many cases, the innovation tax manifests as the inability to even consider new technology because the underlying architecture is too complex and difficult to maintain, much less understand and transform. This is why a lot of senior people at enterprise companies are sitting with their fingers in the transformation dike, waiting for retirement -- they think they can’t modernize. It won’t surprise you that we also saw how MongoDB, as a general purpose database able to handle all types of data at speed and scale, could help solve this problem. Let me be clear. I’ve been working on or with databases for my entire 35-year career, and I joined MongoDB for a reason: I believe we can build the database and application-building environment that I’ve wanted to create and use for at least 30 of those years. Our vision of MongoDB goes beyond our namesake database to a broader, more versatile application data platform that allows you to accelerate and simplify how you build any type of application. It represents significant progress toward our larger goal, which remains the same as ever: to make data stunningly easy to work with. We want to see data become an enabler of innovation, not a blocker. And we want to finally allow technology teams to start to untangle their sprawl and get rid of their DIRT. Where to start? It’s good to have a better understanding of just how DIRT might be holding your teams back. Do your developers have trouble collaborating because the development environment is so fragmented? Do schema changes take longer to roll out than the application changes they’re designed to support? Do you have trouble building 360-degree views of your customers? And if so, why? These are all good places to start digging in the DIRT. You might also take a hard look at your applications and data sources, as well as what it would take to move your data onto an application data platform. That could mean identifying the objects in your applications and all the applications that interact with them. You could then assign a complexity score to each one based on attributes such as properties, methods, collections, and attributes. Now take a step back and identify each application that connects to each of those objects and rank it based on how mission-critical it is, how many people rely on it, how many tasks it has to perform, and the complexity of those tasks. Once you have a better handle on all this complexity, you’ll be better positioned to create a plan to move off your legacy systems, perhaps starting with the least complex and least integrated data sources. Of course, your metrics and your mileage will vary, but the point is to start. I don’t pretend any of this is easy. Like many of you, I’ve spent most of my career working on problems just like these. But that also means I know progress when I see it, and the beginning of a way for organizations to start to clean up their DIRT. I’ll be continuing to write more about these challenges and hopefully continue to add some perspective. If you’re curious to learn more about DIRT, you can download our white paper . As always, I’m eager to have you tweet your alignment, lack thereof, or other thoughts at @MarkLovesTech . You can also reach out to me on marklovestech.com , where you will find a compilation of my latest musings related to MongoDB and otherwise.