Amazon QuickSight vs Apache Spark

Likelihood to Recommend

I'm likely to recommend it because it would become so native if other cloud services are based on AWS infrastructure, like our current setup. It is very seamlessly integrated with other services to feed in data for the visualization. In addition, supporting a reasonably large number of users concurrently is not an issue and should be able to scale horizontally as needed.

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Verified User

Director in Research & Development

Computer Software Company, 51-200 employees

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The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.

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Thomas Young

Owner, previous CEO

Econometric StudiosFinancial Services, 11-50 employees

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Feature Rating Comparison

Amazon QuickSight

Apache Spark

Pixel Perfect reports

Customizable dashboards

Report Formatting Templates

Amazon QuickSight

Customizable Platform (Open Source)

Pros

Lightweight and serverless BI tool that can be used for niche dashboards.
Its integration into other AWS Services is one of its most appealing features.
The low monthly cost is another benefit.

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Verified User

Vice-President in Information Technology

Higher Education Company, 10,001+ employees

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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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Nitin Pasumarthy

Software Engineer

LinkedInInternet, 5001-10,000 employees

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Cons

One of the primary challenges I've had with Amazon QuickSight so far is that some of the reports I want to build use data from different data sets. Instead of being able to put all of the information I want to see into one report.
Some of our Amazon QuickSight reports only update every 24 hours. It would be great to see that data in real-time.
I would remove the various time zones from Amazon QuickSight and only use the time zone we are in.

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Megan Sullivan

Marketing Director

LightRx Face & BodyConsumer Services, 201-500 employees

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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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Anson Abraham

Data Czar

Envisagenics, Inc.Marketing and Advertising, 51-200 employees

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Usability

No score

No answers yet

No answers on this topic

Apache Spark 8.7

Based on 3 answers

Apache integrates with multiple big data frameworks. It does not exert too much load on the disks. Moreover, it is easy to program and use. It reduces the headache of using different applications separately through its high-level APIs. Big data processing has never been as easy as it is with Apache Spark.

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Partha Protim Pegu

Domain Consultant

InfosysInformation Technology & Services, 10,001+ employees

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Support Rating

No score

No answers yet

No answers on this topic

Apache Spark 8.3

Based on 6 answers

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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Yogesh Mhasde

Technical Manager

Rishabh Software Private LimitedInformation Technology & Services, 501-1000 employees

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Alternatives Considered

In our case, we are storing our large amount of data in the cloud so using QuickSight adds up to the performance of the reporting. We are using it as a secondary reporting tool so that a business user can generate their own report. We are using Tableau as our primary reporting tool.

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Verified User

Consultant in Information Technology

Building Materials Company, 501-1000 employees

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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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Verified User

Engineer in Engineering

Computer Software Company, 51-200 employees

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Return on Investment

No answers on this topic

It has had a very positive impact, as it helps reduce the data processing time and thus helps us achieve our goals much faster.
Being easy to use, it allows us to adapt to the tool much faster than with others, which in turn allows us to access various data sources such as Hadoop, Apache Mesos, Kubernetes, independently or in the cloud. This makes it very useful.
It was very easy for me to use Apache Spark and learn it since I come from a background of Java and SQL, and it shares those basic principles and uses a very similar logic.

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Carla Borges

Consultor Tecnico - Java Developer and Php Developer.

Consultec-TIComputer Software, 51-200 employees

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Pricing Details

General

Free Trial

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Free/Freemium Version

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Premium Consulting/Integration Services

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Entry-level set up fee?

No

Amazon QuickSight Editions & Modules

Edition

Authors	$24.00¹
Readers	$5.00¹

Per Month

Additional Pricing Details

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General

Apache Spark

Amazon QuickSight

Apache Spark

Likelihood to Recommend