Category: MongoDB

A Pulse on the Cassandra Community

Posted by on April 08, 2015

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Standing Room Only

I recently attended a Cassandra Day community event. If the crowd was any indication of the install base, I would have to say the interest is strong to quite strong. The weather was miserable in Atlanta and people still managed to show up!

You can spend a lot of time reading articles and various ‘expert’ opinions across the technology world on what is the latest and greatest tool. In addition to reading I would encourage you to collect your own data points and GO TO a community event. You’re able to feel the energy and see first hand the momentum of a product – or lack thereof. Vendor pitches are kept to a minimum and the content tends to be well thought out.

This was my first Cassandra dedicated event but not my first exposure to the Database. The schedule looked typical from the technical side and the morning even included a ‘business’ session that included use-case examples. I made an effort to see a little of both.

The business track was kicked off with your traditional endless amounts of data sales pitches and an introduction to DataStax, the commercial company that offers support and tooling for Cassandra. Standard vendor conference stuff.

So who is using Cassandra? I was pleasantly surprised to hear and learn about companies other than Netflix. Don’t interpret that negatively. Netflix is a great spokesperson for the Cassandra community and helped launch them towards the top of the NoSQL leaderboard. Netflix’s scale is impressive but there is nothing wrong with a little variety. Ask and you shall receive. Target, Safeway and Kroger were all presented as current users.

I found Safeway’s Cassandra use most interesting. They are building an app that takes your shopping list, locates the nearest store and maps product-to-aisle within that store. Cool to see grocery chains embrace technology and try and solve a problem every person has struggled with at one point or another. During the presentation one question stood out in my mind – Why no Mongo? Geolocation has been a very strong use-case for MongoDB since the early days of the product. Unfortunately, the overview was light and the entire story was not shared – but it makes me wonder if Cassandra’s closing the gap on MongoDB faster than what the market perceives.

After DataStax we heard from Asurion (you know, the cell phone insurance folks – you lose or break your phone and they send you a new one for $200), who shared their journey to Cassandra. They followed a typical path through NoSQL enlightenment. RDBMS was failing on scale, along with other things, and they needed a fix.

Asurion’s story: step 1, Postgres to MongoDB. Why didn’t that work for them? It boiled down to lack of understanding MongoDB and assuming it was a drop-in replacement for RDBMS(applying the same relational principles to NoSQL and expecting a better outcome), cites the VP at Asurion. Operational tooling for MongoDB was also another reason why it wasn’t selected. Lack of tooling created a broader challenge when it came to scaling internal resources and their ability to use the tool.

But why Cassandra? DataStax’s operational tooling, analytics strength and scaling capabilities were all mentioned as reasons why – and why they continue to build on Cassandra. I wouldn’t get hung up on the analytics and scale comments since these mean different things to different people. Takeaway, DataStax’s focus on operational tooling continues to be a valuable strategy in gaining new customers.

If MongoDB was evaluated second would it have prevailed? Maybe, Maybe Not.

Data Modeling 101 was the most memorable session for me. When you walk into a large conference room and there are no available seats – you know you’re in for a good session. I’m not exaggerating – there weren’t even the awkward middle seats that people leave open to avoid sitting close to strangers. (see picture at the top)

The speaker was patient and managed the large crowd well. There were plenty of relational modeling to Cassandra modeling references throughout his session.

Now for the recap. So what did I learn?

  • Cassandra’s interest continues to grow
  • DataStax is growing (employees and customers)
  • Hadoop compatibility is top of mind

Cassandra still has ground to catch on MongoDB if you follow db.engines rankings. DataStax growing is good for the community and product evolution. When businesses bet their livelihood on an Apache licensed open source product the community will benefit more often than not. When exploring a new technology the ecosystem can be a great indicator of the current health but DON’T just focus on quantity. The ecosystem is a good indicator of if the technology will a) last and b) prosper. Finally, Hadoop compatibility will continue to be an important piece of the NoSQL conversation and DataStax’s seems to be recognizing that and making it a priority.

It was awesome to see the enthusiasm behind Cassandra in person. NoSQL concepts and products are still new to a lot of people. It is going to take time to make a dent in the RDBMS world but it’s happening. As tools like Cassandra and MongoDB continue to put pressure on the relational databases, users will win. Developers will continue to push database technologies to the limits – therefore forcing products to evolve for the good or disappear.

Building Engaging Customer Experiences Powered by MongoDB

Posted by on July 08, 2014

This spring and summer, the MongoDB Road Show stops in over 20 cities across the country to educate users on how MongoDB can be used to build modern business apps to improve the customer experience and accelerate time to market. Rivet Logic sponsored several of the cities and presented on the topic of building engaging customer experiences with MongoDB, discussing how a modern database can be used to better leverage existing data to derive business value. The next MongoDB Road Show is this Thursday, July 10, in San Francisco!

What Organizations Need

Organizations seeking to build engaging customer experiences on the Web often have a similar set of goals. To start, they want to increase user adoption by providing an engaging experience that brings value to the end-user. This can lead to increased customer retention, allowing organizations to create loyal customers who can then become their own brand ambassadors.

Moreover, organizations want to capitalize on their customers’ and users’ creativity and innovation by seamlessly weaving in the ability to collaborate, interact, and share into every aspect of the user experience. Businesses find the quality of this type of engagement to be particularly beneficial, due to its unpredictability. However, to enhance the value of these interactions, users need a motivator, meaning organizations need to create high quality content that’s personalized and targeted to each user’s needs.

While personas are great and have worked well to capture general types of users, in reality, users think of themselves more as individuals, with evolving interests over time. Organizations are now faced with delivering personalized experiences beyond a persona level and at an individual level.

What’s the Problem?

However, many organizations are having a hard time with this fine-grained personalization, and it’s largely due to the limiting technology they’re working with. IT teams are often faced with seemingly “impractical” features that business teams are requesting.

Organizations today are using separate systems like standalone content apps – blogs, forums, wikis, – commenting engines, traditional databases, and BI tools to enable user interaction and collect and analyze information about them. The quality of user interactions is largely driven by the quality of the user-generated content being collected and analyzed. However, since much of this valuable customer data is silo’d in disparate systems, it’s not allowing businesses to effectively leverage their existing data.

While many have attempted to find workarounds for this, there hasn’t been any real success in creating a coherent rich user interaction data set that brings value to all the delivery use cases available. For example, when a user joins the comment thread of a blog entry, they are unaware of the possibility of a forum thread that is discussing the same topic. In addition, these solutions are typically backed by traditional databases, which requires changing of the infrastructure to accommodate new use cases, posing a challenge.

The fact is, the various types of interactions that exist today are disjointed, resulting in redundancy and little chance of connecting and leveraging them. It’s critical that we make these interactions context-aware, and the only way of effectively doing so is to have a holistic view of all the user-generated content that’s being collected, while also allowing the interactions to cross application boundaries.

Pillars of a Good Solution

Successful solutions that meet these challenges must adhere to the following pillars:

Flexibility – The solution must be implemented using technology agnostic building blocks. Being a certain type of shop (.Net, PHP, Windows, etc.) constrains organizations from using the right tools for the job. Using technology agnostic building blocks as the underlying infrastructure allows organizations to innovate and improve their business without being held back by technology.

Scalability – The solution must be scalable without sacrificing performance. There are many platforms out there that claim to be scalable, but what good is that when scaling means long page load times?

Visibility – It’s also extremely important to be able to know and see the overall picture and have a holistic view of user interactions that isn’t so low-level where it prevents you from seeing what they are doing (as is the case with auditing services).

Insight – Lastly, when you have rich, contextual data available in one place, organizations need to be able to leverage that information, innovate and provide new features, capability, and value to their customers.

Case Study – AT&T Developer Community

Now let’s take a look at how a solution like this might be used in the real world. AT&T is currently undergoing an initiative to build a solution to enhance the user experience of their developer community site. The existing site’s collaboration tools are traditional in nature (i.e. blogs and forums), where user engagement is fragmented, making it difficult to find interesting content and reducing collaboration value.

To resolve this, Rivet Logic is implementing a solution that enables user-generated content to cross application boundaries and reside in one location via Crafter Social, while also allowing for better personalization by using Crafter Profile to maintain a dynamic customer profile.

Crafter Social easily adds social engagement features – user-generated comments, likes, ratings, blogs, discussion forums, and more – to a website by attaching social features to any content item or page. And Crafter Profile provides user profile and account management to help create personalized experiences.

For example, in the current site, if a user comments on a blog entry and another user participates in a forum discussion about the same topic, these interactions are not associated in any way.

With the Crafter Social solution, we were able to turn the blog entry’s comment thread into a virtual forum, thus connecting the two threads of discussion into one. This simple approach is extremely powerful, satisfying all four pillars of a good solution focused on enhancing customer engagement.

Even more, due to Crafter Social’s flexible architecture and underlying data model, it can easily be extended into other use cases, made possible by MongoDB’s document-based data models. In addition, the ability to easily embed Crafter Social into any site using any technology makes it an ideal part of any developer’s toolkit.

As illustrated in the diagram below, Crafter Social is broken into two parts. On the client side, it can be embedded on any site page regardless of what technology was used for implementation. And on the server side, Crafter Social collects various data from different sites and use cases, maintaining a holistic view of the user data. All of this helps enhance the quality of business intelligence information generated.

With this solution, AT&T is able to achieve their goals of increased user adoption and enhanced user engagement and retention. MongoDB plays a key role in the solution’s success by enabling:

  • Flexibility – Create new apps without revisiting infrastructure
  • Scalability – Ability to store large amounts of data and query without hurting performance
  • Visibility – Data is structured in an intuitive way allowing easy translation from raw data to something actionable
  • Insight – Flexible data structures and queries pave the way for creativity and innovation

To download a copy of the slides, click here.