Apache Hadoop vs. Spotfire

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 6.9 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
Spotfire
Score 8.6 out of 10
N/A
Spotfire, formerly known as TIBCO Spotfire, is a visual data science platform that combines visual analytics, data science, and data wrangling, so users can analyze data at-rest and at-scale to solve complex industry-specific problems.
$0.99
Per Hour (Starting)
Pricing
Apache HadoopSpotfire
Editions & Modules
No answers on this topic
Spotfire for Amazon Web Services
$0.99
Per Hour (Starting)
Spotfire Cloud - Consumer
$250/yr
per seat
Spotfire Cloud - Business Author
$650/yr
per seat
Spotfire Cloud - Analyst
$1250/yr
per seat
Spotfire Platform
Please contact Spotfire sales
Spotfire Cloud Enterprise
Please contact Spotfire sales
Offerings
Pricing Offerings
HadoopSpotfire
Free Trial
NoYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFor Enterprise engagements, please contact TIBCO directly for a custom price quote.
More Pricing Information
Community Pulse
Apache HadoopSpotfire
Considered Both Products
Hadoop

No answer on this topic

Spotfire
Chose Spotfire
Tableau definitely does get you to your data faster but it doesn't stack up to Spotfire in overall features.
Chose Spotfire
I have used many different analytics and reporting platforms and Spotfire is among the best, if not the best. It is very user-friendly and intuitive. Spotfire was selected by my organization and I'm glad they did because I think it provides a huge amount of value when it comes …
Top Pros
Top Cons
Features
Apache HadoopSpotfire
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Apache Hadoop
-
Ratings
Spotfire
7.3
8 Ratings
13% below category average
Connect to Multiple Data Sources00 Ratings7.88 Ratings
Extend Existing Data Sources00 Ratings7.48 Ratings
Automatic Data Format Detection00 Ratings7.88 Ratings
MDM Integration00 Ratings6.05 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Apache Hadoop
-
Ratings
Spotfire
9.1
8 Ratings
7% above category average
Visualization00 Ratings9.08 Ratings
Interactive Data Analysis00 Ratings9.28 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Apache Hadoop
-
Ratings
Spotfire
7.4
8 Ratings
10% below category average
Interactive Data Cleaning and Enrichment00 Ratings7.28 Ratings
Data Transformations00 Ratings8.08 Ratings
Data Encryption00 Ratings7.05 Ratings
Built-in Processors00 Ratings7.55 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Apache Hadoop
-
Ratings
Spotfire
7.6
8 Ratings
10% below category average
Multiple Model Development Languages and Tools00 Ratings7.57 Ratings
Automated Machine Learning00 Ratings8.55 Ratings
Single platform for multiple model development00 Ratings7.68 Ratings
Self-Service Model Delivery00 Ratings6.76 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Apache Hadoop
-
Ratings
Spotfire
7.4
7 Ratings
14% below category average
Flexible Model Publishing Options00 Ratings7.87 Ratings
Security, Governance, and Cost Controls00 Ratings7.07 Ratings
Best Alternatives
Apache HadoopSpotfire
Small Businesses

No answers on this topic

Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Mathematica
Mathematica
Score 8.2 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.6 out of 10
Posit
Posit
Score 9.5 out of 10
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User Ratings
Apache HadoopSpotfire
Likelihood to Recommend
8.9
(36 ratings)
8.6
(350 ratings)
Likelihood to Renew
9.6
(8 ratings)
8.7
(30 ratings)
Usability
8.5
(5 ratings)
8.0
(27 ratings)
Availability
-
(0 ratings)
9.0
(14 ratings)
Performance
8.0
(1 ratings)
7.1
(14 ratings)
Support Rating
7.5
(3 ratings)
8.7
(27 ratings)
In-Person Training
-
(0 ratings)
7.7
(52 ratings)
Online Training
6.1
(2 ratings)
8.9
(55 ratings)
Implementation Rating
-
(0 ratings)
8.2
(17 ratings)
Configurability
-
(0 ratings)
7.1
(3 ratings)
Ease of integration
-
(0 ratings)
7.0
(2 ratings)
Product Scalability
-
(0 ratings)
7.0
(4 ratings)
Vendor post-sale
-
(0 ratings)
5.0
(1 ratings)
Vendor pre-sale
-
(0 ratings)
5.0
(1 ratings)
User Testimonials
Apache HadoopSpotfire
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
Read full review
Spotfire
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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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
Read full review
Spotfire
  • 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
Read full review
Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
Read full review
Spotfire
  • 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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Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Spotfire
-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.
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Usability
Apache
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
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Spotfire
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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Reliability and Availability
Apache
No answers on this topic
Spotfire
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.
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Performance
Apache
No answers on this topic
Spotfire
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.
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Support Rating
Apache
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
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Spotfire
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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In-Person Training
Apache
No answers on this topic
Spotfire
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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Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Spotfire
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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Implementation Rating
Apache
No answers on this topic
Spotfire
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.
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Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
Read full review
Spotfire
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.
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Scalability
Apache
No answers on this topic
Spotfire
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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Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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Spotfire
  • 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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ScreenShots

Spotfire Screenshots

Screenshot of Smart Visual AnalyticsScreenshot of Geospatial AnalyticsScreenshot of Intelligent Data WranglingScreenshot of Point-and-click Data ScienceScreenshot of Real-time Streaming Analytics