Apache Spark vs. Qlik Sense

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark
Score 9.0 out of 10
N/A
N/AN/A
Qlik Sense
Score 7.6 out of 10
N/A
Qlik Sense® is a self-service BI platform for data discovery and visualization. It supports a full range of analytics use cases—data governance, pixel-perfect reporting, and collaboration. Its Associative Engine indexes and connects relationships between data points for creating actionable insights.
$20
per month per user (10 user minimum)
Pricing
Apache SparkQlik Sense
Editions & Modules
No answers on this topic
Standard
$20
per month per user (10 user minimum)
Premium
$2700
per month unlimited basic users & purchased full users
Qlik Sense Enterprise on Windows
Contact Sales
Enterprise
Custom Quote
Offerings
Pricing Offerings
Apache SparkQlik Sense
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache SparkQlik Sense
Considered Both Products
Apache Spark

No answer on this topic

Qlik Sense
Chose Qlik Sense
We chose Qlik Sense mostly because:
  • it had an associative engine for analyzing data
  • it was user-friendly
Top Pros
Top Cons
Features
Apache SparkQlik Sense
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
8.5
312 Ratings
4% above category average
Pixel Perfect reports00 Ratings8.3213 Ratings
Customizable dashboards00 Ratings8.9310 Ratings
Report Formatting Templates00 Ratings8.2225 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
8.6
323 Ratings
7% above category average
Drill-down analysis00 Ratings8.9319 Ratings
Formatting capabilities00 Ratings8.2312 Ratings
Integration with R or other statistical packages00 Ratings8.4152 Ratings
Report sharing and collaboration00 Ratings9.0296 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
8.8
275 Ratings
6% above category average
Publish to Web00 Ratings8.8207 Ratings
Publish to PDF00 Ratings8.8254 Ratings
Report Versioning00 Ratings8.8174 Ratings
Report Delivery Scheduling00 Ratings8.8180 Ratings
Delivery to Remote Servers00 Ratings8.8106 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
8.7
311 Ratings
9% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings8.5304 Ratings
Location Analytics / Geographic Visualization00 Ratings8.8281 Ratings
Predictive Analytics00 Ratings8.7193 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
9.0
294 Ratings
6% above category average
Multi-User Support (named login)00 Ratings9.2273 Ratings
Role-Based Security Model00 Ratings9.0270 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.8272 Ratings
Single Sign-On (SSO)00 Ratings8.9216 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
7.5
220 Ratings
4% below category average
Responsive Design for Web Access00 Ratings8.4214 Ratings
Mobile Application00 Ratings8.2132 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings8.2184 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
Apache Spark
-
Ratings
Qlik Sense
8.6
143 Ratings
10% above category average
REST API00 Ratings8.8123 Ratings
Javascript API00 Ratings8.492 Ratings
iFrames00 Ratings8.592 Ratings
Java API00 Ratings8.669 Ratings
Themeable User Interface (UI)00 Ratings8.695 Ratings
Customizable Platform (Open Source)00 Ratings8.482 Ratings
Best Alternatives
Apache SparkQlik Sense
Small Businesses

No answers on this topic

BrightGauge
BrightGauge
Score 8.9 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Reveal
Reveal
Score 10.0 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.7 out of 10
Jaspersoft Community Edition
Jaspersoft Community Edition
Score 9.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SparkQlik Sense
Likelihood to Recommend
9.3
(24 ratings)
8.5
(327 ratings)
Likelihood to Renew
10.0
(1 ratings)
8.4
(7 ratings)
Usability
8.6
(4 ratings)
8.0
(11 ratings)
Support Rating
8.7
(4 ratings)
7.3
(8 ratings)
In-Person Training
-
(0 ratings)
9.1
(1 ratings)
Online Training
-
(0 ratings)
9.1
(1 ratings)
Implementation Rating
-
(0 ratings)
7.3
(5 ratings)
Vendor post-sale
-
(0 ratings)
9.1
(1 ratings)
Vendor pre-sale
-
(0 ratings)
9.1
(1 ratings)
User Testimonials
Apache SparkQlik Sense
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.
Read full review
Qlik
Qlik Sense is a program whose purpose is to greatly improve all your operations and use of all data in an organic way. The mission will always be to increase the economic and commercial processes of the company in a short time. I recommended it for its high technology, which was Created for this area, the results are successful. We have noticed how it has increased relationships with our clients thanks to the credibility and security that we provide.
Read full review
Pros
Apache
  • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
  • Faster in execution times compare to Hadoop and PIG Latin
  • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
  • Interoperability between SQL and Scala / Python style of munging data
Read full review
Qlik
  • Flexibility in data recording, from the app, as well as in handling them. Allowing you to view reports quickly and effectively.
  • Easy to generate dynamic graphics according to our needs.
  • It is very easy to use, intuitive, so it does not generate costs in the learning process compared to the tool with collaborators
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
  • Scalability is RAM limited, all data is associative and in-memory so server's RAM is directly proportional to performance
  • Limitation on advanced analytics capabilities in the form of R integration to perform complex statistical and analytical calculations
  • Can have more intuitive interface
Read full review
Likelihood to Renew
Apache
Capacity of computing data in cluster and fast speed.
Read full review
Qlik
Qlik Sense is a constantly improving it's software and working with its' users to make it better. They are great at keeping their users informed of progress and care about delivering a quality product
Read full review
Usability
Apache
If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used
Read full review
Qlik
Standard user interface and powerful analytic functions is GREAT. As technical person working in the background there are more things to do to make this a completely great tool. Some functions that should be standard requires consult scripting and hours. Now we are using it quite advanced and with many servers and in combination with QlikView. So overall I love the tool. But it could be better and user friendly and powerful in the background
Read full review
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.
Read full review
Qlik
Not only can you ask the support team for help, but you can also ask the community. Also with the community there is a vast amount of problems that have already been solved. The problem you are encountering has a likely chance of already being discussed and even solved in the community section saving you time from reaching out.
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In-Person Training
Apache
No answers on this topic
Qlik
The instructor was very knowledgeable.
Read full review
Online Training
Apache
No answers on this topic
Qlik
The online instructor was very knowledgeable.
Read full review
Implementation Rating
Apache
No answers on this topic
Qlik
Hire Qlik consultants. It's better done by them or with their aid.
Read full review
Alternatives Considered
Apache
Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.
Read full review
Qlik
The customization of the platform opens up plenty of other options depending on the use cases. The API layer is incredibly rich and makes integration of Qlik based visualization into web pages a simple and effective pattern. It's been very easy to use with a great community made up of professionals. Qlik Sense has introduces artificial Intelligence into my data visualization and reporting activity.
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Return on Investment
Apache
  • Business leaders are able to take data driven decisions
  • Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
  • Business is able come up with new product ideas
Read full review
Qlik
  • Once an app is published and running good, we can quickly see the time we save to analyze data.
  • It's hard sometimes to realize the money we save by using this system.
  • People start understanding the power of data and asking more questions.
Read full review
ScreenShots

Qlik Sense Screenshots

Screenshot of Qlik Sense Cash Flow DashboardScreenshot of Qlik Sense Global Smart SearchScreenshot of Qlik Sense Smart Data Compression - Get immediate insight on large dataScreenshot of Extend, mix and mash-up with our APIsScreenshot of Add "External data" with Qlik DataMarket - Data as a ServiceScreenshot of Visualization Bundle