MongoDB vs. Webtrends Analytics

If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.

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Scenarios 1. If you want to use web server log files as input to your web analytics, then Webtrends will provides a good product, with great ease of implementation. Don't even think about being cheap on hardware, and make sure Webtrends runs on real servers, not in a VM environment. 2. If you want to use Data Tagging, similar to Google Analytics or Site Catalyst, Webtrends has a powerful product, just be prepared to pay. 3. If you are new to Web Analytics, but it is the strategic direction, start with Webtrends on Premises. Questions to Ask 1. What are you trying to accomplish? 2. Can you place a dollar value on the benefit that you expect/need from Webtrends? 3.Can you live with Webtrends running SaaS?

• Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
• You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
• Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.

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• Control privacy, data sharing and competitive industrial knowledge using Webtrends on premises
• Great control over custom reports, custom dimensions and metrics
• Flexible tool which allows multiple methods of data capture. To my knowledge it was the first tool with a Tag Builder / Tag Management function built in via a supporting website.

• An aggregate pipeline can be a bit overwhelming as a newcomer.
• There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
• Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.

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• The big downside, the elephant in the room, is that it does not (as of right now) have on-demand segmenting, drilldowns, etc. You have to think of what you want in advance and create those reports then analyze some data. This is huge. You can, of course, re-analyze old data after creating new reports but you still have to wait. (This deficiency may become obsolete with the release of Webtrends Explore later this month (May 2014).)
• It has fewer mature integrations with other products and databases than competitors do, although I'm told it works with SharePoint better than anything else does.
• Its attribution modeling capability is behind Google Analytics'. In my humble opinion, this could be changed quickly if Webtrends would make some tweaks to its standard visitor history files (i.e. preserve the order in which past visits were sourced beyond the single most recent one, rather than storing all those past sources as a randomized list).
• It doesn't incorporate statistical tests, confidence intervals, or statistical associations. However, this same criticism can be applied to its competitors (other than A/B Testing products). It's a tabulation program, as they all are. In this respect, web analytics tools as a group are relatively primitive. Sorry to bring this up as a criticism of Webtrends but it's my pet peeve about the whole industry and I just have to say it. (p.s. take advantage of the heavy-duty Webtrends Scheduled Export functionality to get really granular data that you can feed to a stats program to get significances.)
• Although the documentation, help screens, phone support and the knowledge base have improved tremendously in recent years, there is still a pretty steep learning curve because it is different from the tools that entry-level users may have already been exposed to. This can be a shock and many users are alienated at first because they just don't get some of the fundamentals at first. I'd like to see much better help screens that are thoroughly interlinked with the KB and documentation. Having superb online support would make a world of difference with the adoption of this basically powerful tool.

I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.

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I would be willing to try Webtrends again AFTER some research from other users. I would need to see that users mention better and faster customer support on questions and issues that arise while using the software. The software is capable of vast and incredible things, but if it isnt properly set up and supported during use, it is just a big hassel and waste of everyones time and money.

NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.

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If I could give it a 0, I would. Not having an intuitive user interface made it impossible to convince non-analytic business users to use the tool on their own. Even as a seasoned analyst, frequent calls were needed to get what should be simple tasks done. Account managers don't understand the tool either, and have to refer you to technical support

It is much better than average. Down time usually occurs because of a need to refresh the server on our end.

The v9 admin interface and v10 reporting interface work as well as expected, but have a tendency to be pokey, especially for bulky reports and whenever you're connected to wifi. I much prefer using the REST API for all reporting for this reason, which simply dumps out the data and doesn't bother with the user interface.

Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.

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I once went on to Twitter to ask for help from my network of analytics people, and Webtrends themselves responded. They have been an excellent partner in making sure that their product is being used to the best of it's ability and I greatly appreciate that. Both Omniture and Google Analytics, do not have that level of support over social media

The in-person training was comprehensive enough to get you started, but I strongly recommend having a more experienced person when beginning with the tool.

Webtrends provides several free webinars over the course of the year, many of which I would expect to pay for. The people providing the webinars seem to have a good feel for real-world application of the product.

While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.

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Careful planning and patience. Use a non-public test site to fine tune tags and reporting. Despite best laid plans, there will be surprises when you collect the data, run the analysis and begin generating reports using the tool. Perform a tag audit to ensure tags fire as desired.

We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.

Webtrends has its work cut out for itself considering you have the behemoth Google Analytics and Google Analytics Premium having a strong offering and brand recognition for the price of free. After reviewing the paid service I'd suggest you start off with GA as a cheaper alternative that is just as robust, if not much more flexible in regards to the reporting and goal tracking needs for our company.

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• Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
• You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB

• Webtrends has had a positive impact on site visitation because it allowed us to understand the sources by domain for site traffic and find out ways to increase visits from those domains.
• Webtrends has also allowed us to understand areas of optimization on the site, which has had a positive impact on the overall user journey on the site, likely leading to longer site duration and engagement.