Apache Spark vs. QlikView

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark
Score 8.7 out of 10
N/A
N/AN/A
QlikView
Score 8.0 out of 10
N/A
QlikView® is Qlik®’s original BI offering designed primarily for shared business intelligence reports and data visualizations. It offers guided exploration and discovery, collaborative analytics for sharing insight, and agile development and deployment.N/A
Pricing
Apache SparkQlikView
Editions & Modules
No answers on this topic
QlikView
Custom
per user
Offerings
Pricing Offerings
Apache SparkQlikView
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional DetailsOn an perpetual license basis, based on server plus number of users. Contact vendor for pricing.
More Pricing Information
Features
Apache SparkQlikView
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Apache Spark
-
Ratings
QlikView
8.0
67 Ratings
2% below category average
Pixel Perfect reports00 Ratings8.049 Ratings
Customizable dashboards00 Ratings8.065 Ratings
Report Formatting Templates00 Ratings8.059 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Apache Spark
-
Ratings
QlikView
8.3
66 Ratings
3% above category average
Drill-down analysis00 Ratings9.065 Ratings
Formatting capabilities00 Ratings7.066 Ratings
Integration with R or other statistical packages00 Ratings8.336 Ratings
Report sharing and collaboration00 Ratings9.061 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Apache Spark
-
Ratings
QlikView
7.9
61 Ratings
5% below category average
Publish to Web00 Ratings8.048 Ratings
Publish to PDF00 Ratings9.056 Ratings
Report Versioning00 Ratings7.542 Ratings
Report Delivery Scheduling00 Ratings7.347 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Apache Spark
-
Ratings
QlikView
7.3
57 Ratings
10% below category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings7.754 Ratings
Location Analytics / Geographic Visualization00 Ratings7.546 Ratings
Predictive Analytics00 Ratings6.85 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Apache Spark
-
Ratings
QlikView
8.2
59 Ratings
4% below category average
Multi-User Support (named login)00 Ratings8.558 Ratings
Role-Based Security Model00 Ratings8.054 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.054 Ratings
Report-Level Access Control00 Ratings8.52 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
Apache Spark
-
Ratings
QlikView
8.0
47 Ratings
0% above category average
Responsive Design for Web Access00 Ratings8.044 Ratings
Mobile Application00 Ratings9.028 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings8.038 Ratings
Best Alternatives
Apache SparkQlikView
Small Businesses

No answers on this topic

BrightGauge
BrightGauge
Score 9.0 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Reveal
Reveal
Score 9.9 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
Jaspersoft Community Edition
Jaspersoft Community Edition
Score 9.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SparkQlikView
Likelihood to Recommend
9.9
(24 ratings)
8.5
(87 ratings)
Likelihood to Renew
10.0
(1 ratings)
8.8
(29 ratings)
Usability
10.0
(3 ratings)
8.2
(14 ratings)
Availability
-
(0 ratings)
9.8
(4 ratings)
Performance
-
(0 ratings)
8.6
(4 ratings)
Support Rating
8.7
(4 ratings)
3.4
(15 ratings)
Online Training
-
(0 ratings)
8.0
(3 ratings)
Implementation Rating
-
(0 ratings)
7.4
(13 ratings)
Product Scalability
-
(0 ratings)
8.9
(2 ratings)
User Testimonials
Apache SparkQlikView
Likelihood to Recommend
Apache
Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
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Qlik
Sales data validations have helped manage our justifications in the past, especially with regard to new product development and new business introduction. It has also been helpful in identifying trends with business impact and direction specific to quarter and monthly sales from ERP data as well as decisions to purchase equipment of staffing based on run rates and product demand.
One thing that can get out of hand is data output - if you aren't careful in your query, you may be overloaded with data dumps and drown in the amount of info you have to filter through. This is a user caution, not a comment on the software itself.
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Pros
Apache
  • Apache Spark makes processing very large data sets possible. It handles these data sets in a fairly quick manner.
  • Apache Spark does a fairly good job implementing machine learning models for larger data sets.
  • Apache Spark seems to be a rapidly advancing software, with the new features making the software ever more straight-forward to use.
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Qlik
  • QlikView has a simple, relational data model that's REALLY fast. Filtering and changing data is dead simple results are almost immediately available.
  • The free version of Qlikview is almost completely featured, so you roll a pro-level product out to an entire department for really cheap.
  • QlikView is really flexible--if you can imagine it, you can build it.
Read full review
Cons
Apache
  • Memory management. Very weak on that.
  • PySpark not as robust as scala with spark.
  • spark master HA is needed. Not as HA as it should be.
  • Locality should not be a necessity, but does help improvement. But would prefer no locality
Read full review
Qlik
  • We found that QlikView can be a bit slow in supporting some forms of encryption. It is web-based and we needed to upgrade all of our server to not support the older SSL and TLS 1 protocols, only support TLS 1.2 and TLS 1.3. However, QlikView could not run with TLS 1.2 and TLS 1.3. We had to wait over six months to get a version that would handle the newer TLS versions.
  • There are so many options with QlikView that you can get lost when developing a visualization. There are still items I have not yet figured out, such as labeling a graph with the name of a selected detail item.
  • QlikView works by pulling the data it is going to use for visualization into its database. I am a security reviewer and I need to make certain that PII and PHI is not pulled by QlikView for a visualization, otherwise this could become a reportable indecent.
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Likelihood to Renew
Apache
Capacity of computing data in cluster and fast speed.
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Qlik
Ease of use, ability to load from pretty much any data source. today I created an application that loaded time sheets from excel that are not in a table format. With Qlik's "enable transformation steps" I was able to automate loads of multiple spreadsheets and multiple tabs easily. Could not do that with any other tool.
Read full review
Usability
Apache
The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.
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Qlik
QlikView is very easy to implement. The installation is very straight forward. QlikView has several different data connectors that can connect to different data sources very smoothly. The user interface to build the reports is very easy to understand. This helps to have a smaller learning curve. Something very helpful is that QlikView is a browser application for the end users. So, you don't need to install any applications on the user's computer.
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Reliability and Availability
Apache
No answers on this topic
Qlik
We have not had any downtime issues with the product nor uncovered any significant bugs
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Performance
Apache
No answers on this topic
Qlik
It is not a SAAS product.
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Support Rating
Apache
1. It integrates very well with scala or python. 2. It's very easy to understand SQL interoperability. 3. Apache is way faster than the other competitive technologies. 4. The support from the Apache community is very huge for Spark. 5. Execution times are faster as compared to others. 6. There are a large number of forums available for Apache Spark. 7. The code availability for Apache Spark is simpler and easy to gain access to. 8. Many organizations use Apache Spark, so many solutions are available for existing applications.
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Qlik
My experience with the Qlik support team has been somewhat limited, but every interaction I have had with them has been very professional and I received a response quickly. Typically if there is a technical issue, our IT team will follow up. My inquiries are specific to product functionality, and Qlik has been very helpful in clarifying any questions I might have.
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In-Person Training
Apache
No answers on this topic
Qlik
My team attended, but I cannot myself rate, but I think it was good as they've successfully launched a training program at our company themselves for users. It was 3-4 day training.
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Online Training
Apache
No answers on this topic
Qlik
Training was as expected. The demo environments tend to be more fully featured that our own environment, but the training was clear and well delivered.
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Implementation Rating
Apache
No answers on this topic
Qlik
"Implementation" can mean a few things... so I'm not sure that this is the answer you want.... but here it goes: To me, implementation means: "Is the user interface intuitive and can I produce meaningful reports with ease?" On that score, I'd say YES. The amount of training required was minimal and the results were powerful. The desktop implementation is a simple, "blank" interface just waiting for your creativity. The pre-populated templates give you a reasonable start to any project -- and a good set of objects to "play around with" if you're just getting started. Finally, note that the "implementation" I used was baked into QuickBooks 2016 Enterprise -- called "Advanced Reporting"..... That integration makes it ultra useful and simple.
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Alternatives Considered
Apache
All the above systems work quite well on big data transformations whereas Spark really shines with its bigger API support and its ability to read from and write to multiple data sources. Using Spark one can easily switch between declarative versus imperative versus functional type programming easily based on the situation. Also it doesn't need special data ingestion or indexing pre-processing like Presto. Combining it with Jupyter Notebooks (https://github.com/jupyter-incubator/sparkmagic), one can develop the Spark code in an interactive manner in Scala or Python
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Qlik
The only other vendor product that I have worked with that provides a similar experience to Qlikview is Tableau. I would recommend Tableau if your use case is to build a fixed dashboard. You can share reports for free without needing to buy additional licenses. I would recommend Qlikview if your users are looking for a more interactive experience. They can create new objects to represent the data which can't be accomplished as easily in Tableau
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Return on Investment
Apache
  • Faster turn around on feature development, we have seen a noticeable improvement in our agile development since using Spark.
  • Easy adoption, having multiple departments use the same underlying technology even if the use cases are very different allows for more commonality amongst applications which definitely makes the operations team happy.
  • Performance, we have been able to make some applications run over 20x faster since switching to Spark. This has saved us time, headaches, and operating costs.
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Qlik
  • You can use the free desktop version to do a lot of reporting and analysis work more quickly so the ROI is huge
  • QlikView is great at finding outliers such as data entry errors
  • QlikView is great at helping you quickly discover new insights about your business that can prompt you to take action that can immediately affect your cash flow.
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ScreenShots

QlikView Screenshots

Screenshot of QlikView Sales DashboardScreenshot of QlikView on all devicesScreenshot of QlikView using mobile touch screen