Spotfire vs. Zabbix

A high level of data integration is available here it supports various data sources and so on. Collaborating features allow users to give access to the dashboard and merge data analytics with other team members. It can meet the demands of both small and large size business enterprises. A customized dashboard and reports are provided to meet the specific needs and get support of extensibility through APIs and customized scripts.

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Zabbix is great for monitoring your servers and seeing alerts when the system uses too much CPU or memory. This allowed the system Engineer to be proactive and add resources to these systems to avoid interrupting the services. Especially servers running operations applications and services. This is one of the best usages for Zabbix.

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• It has the best coding integration (python, R) of any BI product
• The ability to work with very large datasets (10 mil+) is better than competitors
• Export options are more complete and have better functionality
• The data canvas is the best tool to join and transform data vs. competitors

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• Collecting hardware data - CPU, Memory, Network, and Disk Metrics are collected and reported on.
• Flexible design - It is very easy to build out even very large environments via the templating system. You can also start where you are - network monitoring, server monitoring, etc. and then build it out from there as time and resources permit.
• Provides a "plugin architecture" (via XML templates) to allow end users to extend it to monitor all kinds of equipment, software, or other metrics that are not already added into the software already.
• Very complete documentation. Almost every aspect of Zabbix has been documented and reported on.
• Cost - Zabbix is FOSS software and always free. Support is reasonably priced and readily available.

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• The donut chart is I guess a powerful illustrations but I hope it should be done quite simple in Spotfire. But in Spotfire there are lots of steps involve just to build a simple donut chart.
• Table calculation (like Row or Column Differences) should be made simple or there should be drag and drop function for Table Calculation. No need for scripting.
• Information Link should be changed. If new columns are added to the table just refreshing the data should be able to capture the new column. No need extra step to add column

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• Creating an alert & its trigger can be made easier.
• More VM-based data collection counters should be introduced to have better VM monitoring.
• The raw counters collection agent in every node is relatively weak. It goes down often, which needs more stability.

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-Easy to distribute information throughout the enterprise using the webplayer. -Ad hoc analysis is possible throughout the enterprise using business author in the webplayer or the thick client. -Low level of support needed by IT team. Access interfaces with LDAP and numerous other authentication methods. -Possible to continually extend the platform with JavaScript, R scripts, HTML, and custom extensions. -Ability to standardize data logic through pre-built queries in the Information Designer. Everyone in the enterprise is using the same logic -Tagging and bookmarking data allows for quick sharing of insights. -Integration with numerous data sources... flat files, data bases, big data, images, etc. -Much improved mapping capability. Also includes the ability to apply data points over any image.

It is free. It didn't cost anything to implement (other than my time and the cost incurred for it) and it is filling a badly needed gap in our IT infrastructure. Support is available if we have issues and can be done annually or paid for on a per incident basis as needed. Expansion, updates, and all other future lifecycle activities are likewise free of cost, so as long as someone is able to implement/maintain the software (and the OSS project is maintained) then I imagine the company will never leave it.

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Basic tasks like generating meaningful information from large sets of raw data are very easy. The next step of linking to multiple live data sources and linking those tables and performing on the fly analysis of the imported data is understandably more difficult.

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I think every organization, especially the IT department, needs a tool like this. I know of another product like Zabbix that gives a similar or the same solution, but its range makes it very useful. You can see almost all the device info in one place: disk usage, disk space, network usage, etc.

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Even though, it's a rather stable and predictable tool that's also fast, it does have some bugs and inconsistencies that shut down the system. Depending on the details, it could happen as often as 2-3 times a week, especially during the development period.

Generally, the Spotfire client runs with very good performance. There are factors that could affect performance, but normally has to do with loading large analysis files from the library if the database is located some distance away and your global network is not optimal. Once you have your data table(s) loaded in the client application, usually the application is quite good performance-wise.

Support has been helpful with issues. Support seems to know their product and its capabilities. It would also seem that they have a good sense of the context of the problem; where we are going with this issue and what we want the end outcome to be.

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The setup is the most time-consuming portion of using zabbix. It takes a lot of effort to shape it into a usable format and even then it can get very messy. It's not exactly intuitive and as mentioned the UI seems a bit antiquated. If I was to roll out a monitoring solution from scratch, I'd probably look for alternatives which are easier to use and maintain.

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The instructor was very in depth and provided relevant training to business users on how to create visualizations. They showed us how to alter settings and filter views, and provided resources for future questions. However, the instructor failed to cover data sources, connecting to data, etc. While it was helpful to see how users can use the data to create reports, they failed to properly instruct us on how to get the dataset in to begin with. We are still trying to figure out connections to certain databases (we have multiple different types).

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The online training is good, provides a good base of knowledge. The video demonstrations were well-done and easy to follow along. Provided exercises are good as well, but I think there could be more challenging exercises. The training has also gone up in price significantly in the last 3 years (in USD, which hurts us even more in Canada), and I'm not sure it is worth the money it now costs (it is worth how much it cost 3 years ago, but not double that.)

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The original architecture I created for our implementation had only a particular set of internal business units in mind. Over the years, Spotfire gained in popularity in our company and was being utilized across many more business units. Soon, its usage went beyond what the original architectural implementation could provide. We've since learned about how the product is used by the different teams and are currently in the middle of rolling out a new architecture. I suggest:

• Have clearly defined service level agreements with all the teams that will use Spotfire. Your business intelligence group might only need availability during normal working hours, but your production support group might need 24/7 availability. If these groups share one Spotfire server, maintenance of that server might be a problem.
• Know the different types of data you will be working with. One group might be working with "public" data while another group might work with sensitive data. Design your Library accordingly and with the proper permissions.
• Know the roles of the users of Spotfire. Will there only be a small set of report writers or does everyone have write access to the Library?
• ALWAYS add a timestamp prompt to your reports. You don't want multiple users opening a report that will try and pull down millions of rows of data to their local workstations. Another option, of course, is to just hard code a time range in the backing database view (i.e. where activity_date >= sysdate - 90, etc.), but I'd rather educate/train the user base if possible.
• This probably goes without saying, but if possible, point to a separate reporting database or a logical standby database. You don't want the company pounding on your primaries and take down your order system.

We are a mainly Windows environment, so it would be useful if we could have used Active Directory to deploy agents. As of version 4.2, Zabbix has announced a new agent MSI file to allow exactly that. Unfortunately, we didn't have that option. Also, for Linux and MAC deployments, there is no simple way to deploy that. Using remote scripts you may be able to create something, but most places will opt for either SNMP (agentless) or manual installation of agents to add to Zabbix. A way of deploying agents via discovery would go a long way to helping in the adoption of the tool.

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Spotfire is significantly ahead of both products from an ETL and data ingestion capability. Spotfire also has substantially better visualizations than Power BI, and although the native visualizations aren't as flexible in Tableau, Spotfire enables users to create completely custom javascript visaualizations, which neither Tableau or Power BI has. Tableau and Power BI are likely only superior to Spotfire with respect to embedded analysis on a website.

We're using the Solarwinds suite as our global monitoring standard, but it is very complex and its licensing model makes it difficult to monitor a wide range of technologies. So, we're using Zabbix as a complement on our monitoring process. Zabbix is a way more flexible and has free integrations to a wide range of technologies. It is also more 'user friendly' and easy to manage.

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In an enterprise architecture, if Spotfire Advanced Data services(Composite Studio),data marts can be managed optimally and scalability in a data perspective is great. As the web player/consumer is directly proportional to RAM, if the enterprise can handle RAM requirement accomodating fail over mechanisms appropraitely, it is definitely scalable,

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• It is costly, so not suitable for small scale implementations.
• Dashboards are as good as the developer, so need experience to get most out of it
• You need to be on Spotfire 11 at least to implement out of the box visualizations
• Integration with Python and R is a game changer, it comes very handy to onboard data scientists without much hassle
• performance is exceptionally well.
• Secure

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• Good ROI when trying to get ahead of network related problems instead of waiting for users to complain
• Good ROI when doing upgrades or exploratory work on a neglected network
• Good ROI when showing usage trends to management showing higher actual usage versus what was thought to be happening