Alteryx Platform vs. Apache Spark

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Alteryx Platform
Score 9.1 out of 10
N/A
The Alteryx AI Platform gives organization automated data preparation, AI-powered analytics, and machine learning with embedded governance and security. Its self-service functionality, with self-service data prep, machine learning, and AI-generated insights, gives enterprise teams with a simplified user experience allowing everyone to create analytic solutions that improve productivity, efficiency, and the bottom line. Alteryx Designer can be used to automate every analytics step…
$14,850
per year 3 users (minimum), cloud edition
Apache Spark
Score 9.0 out of 10
N/A
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.N/A
Pricing
Alteryx PlatformApache Spark
Editions & Modules
Designer Desktop
starting at $5,195
per year per user
Designer Cloud Professional Edition
Starting at $4,950
per year per user (minimum of 3 users)
No answers on this topic
Offerings
Pricing Offerings
Alteryx PlatformApache Spark
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Alteryx PlatformApache Spark
Best Alternatives
Alteryx PlatformApache Spark
Small Businesses
IBM SPSS Statistics
IBM SPSS Statistics
Score 8.1 out of 10

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Medium-sized Companies
JMP
JMP
Score 9.5 out of 10
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Enterprises
JMP
JMP
Score 9.5 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.2 out of 10
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User Ratings
Alteryx PlatformApache Spark
Likelihood to Recommend
9.1
(138 ratings)
9.0
(24 ratings)
Likelihood to Renew
8.8
(19 ratings)
10.0
(1 ratings)
Usability
9.1
(53 ratings)
8.0
(4 ratings)
Availability
7.3
(4 ratings)
-
(0 ratings)
Performance
8.8
(45 ratings)
-
(0 ratings)
Support Rating
9.2
(52 ratings)
8.7
(4 ratings)
In-Person Training
7.0
(1 ratings)
-
(0 ratings)
Online Training
8.6
(2 ratings)
-
(0 ratings)
Implementation Rating
8.0
(5 ratings)
-
(0 ratings)
Configurability
7.3
(2 ratings)
-
(0 ratings)
Ease of integration
8.2
(3 ratings)
-
(0 ratings)
Product Scalability
7.3
(3 ratings)
-
(0 ratings)
Vendor post-sale
8.2
(2 ratings)
-
(0 ratings)
Vendor pre-sale
7.3
(1 ratings)
-
(0 ratings)
User Testimonials
Alteryx PlatformApache Spark
Likelihood to Recommend
Alteryx
I would 100% recommend Alteryx to a friend, for me its friendly interface is the best, it has all the tools I need without the headache that programming is. It can be used for simple or complex analysis, so honestly, I don’t see a scenario where it wouldn’t suit. I’ve used Alteryx to make simple things I could do in Excel, for example, but it was less complex and faster to do in Alteryx, so why not? Its a very versatile tool.
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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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Pros
Alteryx
  • Pulling data from multiple disparate data sources.
  • Allows users to see the data at every step of the workflow to be able to cleanse, analyze, and optimize the data.
  • Provides an analytics platform that is easy for users of all levels to thrive in whether they are just starting out in their analytics journey or they have a master's degree in Data Science.
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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
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Cons
Alteryx
  • Steeper Learning Curve: Alteryx can have a steep learning curve for users who are new to the platform or have limited experience with data analytics. Enhancements to the user interface and user onboarding resources could help make the learning process more intuitive and accessible to a wider range of users.
  • Enhanced Data Visualization Capabilities: Alteryx offers basic data visualization capabilities, but there is room for improvement in terms of advanced visualizations and interactive dashboarding features. Adding more sophisticated chart types, interactive widgets, and customization options would enhance the data visualization capabilities within the platform.
  • Improved Error Handling and Debugging: Alteryx provides error handling mechanisms, but enhancing the error reporting and debugging capabilities would be beneficial. Improved error messages, better visibility into data flow, and debugging tools could help users troubleshoot and resolve issues more efficiently.
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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
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Likelihood to Renew
Alteryx
We've developed a working partnership with Alteryx. As an enablement suite, we're continuing to innovate and deliver great products with use of Alteryx in our solutions. Alteryx use expands to our global product development teams and is in use in multiple parts of our organization. Alteryx also delivers Experian demographic content to other clients in their product offering. We're highly likely to renew, but that decision is way above my pay grade.
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Apache
Capacity of computing data in cluster and fast speed.
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Usability
Alteryx
I've found that while some things might take a little longer to create, the flexibility of Alteryx allows you to perform any function needed. I haven't found a use that was not available in Alteryx yet. APIs and XMLs can be created to perform certain functions. In addition, CMD line commands can be sent using Alteryx to perform certain functions as well.
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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
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Reliability and Availability
Alteryx
I use many programs and compared to others, Alteryx virtually never goes down, freezes up or gives an application error. Over a 4 year time period that I have used this program, any of these may have happened 3 times. It is an incredibly stable program that I feel completely confident in.
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Apache
No answers on this topic
Performance
Alteryx
I already gave the example of journal entries created in less than a second. What else can I tell you about.... I can tell you those 2 journal entries have historically had to be split into separate accounting systems so the outputs had to be very different (D365 vs Intacct) such that they are exactly ready for uploading. I can tell you I used to have some tire and battery queries hitting a line item detail table and they took hours to run UNTIL I asked IT for a view in SQL and now they're ready in about 5 minutes total. I guess I'd say if anything does take a long time - do some research with others and figure out what would speed them up
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Apache
No answers on this topic
Support Rating
Alteryx
Stellar, bar-none. Some of the best support folks of any vendor. The Alteryx Community is the most responsive and supportive. On the rare occasion of a release issue or bug, we've been able to get quick help to solve the core problem. Alteryx does not play the blame game. They genuinely help the users solve their issues or respond to questions
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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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In-Person Training
Alteryx
1st level of trainings which I've attended in Paris was easy and I was already knowing %90, that learning could have been an e-learning instead of in-person
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Apache
No answers on this topic
Online Training
Alteryx
Very good, detailed online trainings which you can take at your own pace, and strong certifications exists, certifications are extremely detailed and hard...
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Apache
No answers on this topic
Implementation Rating
Alteryx
There is really not much to it (the installation, that is). Once you get it installed, along with any of the add-ons (demographics, R, etc.), you are up and running almost immediately. There is really no additional setup. You can immediately begin blending data, running demographics, performing spatial queries, running predictive analysis, etc. And for many of these functions, the learning curve is quite easy.
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Apache
No answers on this topic
Alternatives Considered
Alteryx
Alteryx is MUCH more user friendly. both provide the ability to code within them, but Alteryx has much nicer interface. The formula tools have a more simple language that is easier to learn than formulae in SSIS. Alteryx is easy to read with multi colored tools identifying what each one does. It also allows for macros. You can build your own tool to process records of data or batch records together.
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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.
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Scalability
Alteryx
Individual analysts can quickly generate results using their own copy of Alteryx Designer. But using the Server and developing macros for more complex needs can be time consuming.
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Apache
No answers on this topic
Return on Investment
Alteryx
  • Error handling - allows controls to be built into workflows easily and allows them to be isolated and spat into control reports that can be easily reviewed and audited, thanks to the ability to create multiple outputs in one go.
  • Time-saving - saved huge amounts of time, especially when moving Excel processes into Alteryx.
  • Product development - allowed my firm to create products that we have been able to market and sell to clients.
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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
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ScreenShots

Alteryx Platform Screenshots

Screenshot of Alteryx APA - Automating asset inputsScreenshot of Alteryx APA - Automating outcomesScreenshot of Alteryx APA - Data enrichment and insightsScreenshot of Alteryx APA - Data quality and preparationScreenshot of Alteryx APA - Data science and decisions