Apache Spark vs Data Science Workbench

Likelihood to Recommend

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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Organizations which already implemented on-premise Hadoop based Cloudera Data Platform (CDH) for their Big Data warehouse architecture will definitely get more value from seamless integration of Cloudera Data Science Workbench (CDSW) with their existing CDH Platform. However, for organizations with hybrid (cloud and on-premise) data platform without prior implementation of CDH, implementing CDSW can be a challenge technically and financially.

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Verified User

Professional in Information Technology

Telecommunications Company, 1001-5000 employees

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Feature Rating Comparison

Apache Spark

Data Science Workbench

Connect to Multiple Data Sources

Extend Existing Data Sources

Automatic Data Format Detection

MDM Integration

Apache Spark

Data Science Workbench

Visualization

Interactive Data Analysis

Apache Spark

Data Science Workbench

Interactive Data Cleaning and Enrichment

Data Transformations

Data Encryption

Built-in Processors

Apache Spark

Data Science Workbench

Multiple Model Development Languages and Tools

Automated Machine Learning

Single platform for multiple model development

Self-Service Model Delivery

Apache Spark

Data Science Workbench

Flexible Model Publishing Options

Security, Governance, and Cost Controls

Pros

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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One single IDE (browser based application) that makes Scala, R, Python integrated under one tool
For larger organizations/teams, it lets you be self reliant
As it sits on your cluster, it has very easy access of all the data on the HDFS
Linking with Github is a very good way to keep the code versions intact

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Bharadwaj (Brad) Chivukula

Sr.Technical Manager/Delivery Manager

Nisum Technologies, Inc.Retail, 10,001+ employees

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Cons

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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Installation is difficult.
Upgrades are difficult.
Licensing options are not flexible.

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Verified User

Professional in Research & Development

Utilities Company, 10,001+ employees

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Usability

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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No score

No answers yet

No answers on this topic

Support Rating

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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Data Science Workbench 7.1

Based on 2 answers

Cloudera Data Science Workbench has excellence online resources support such as documentation and examples. On top of that the enterprise license also comes with SLA on opening a ticket to Cloudera Services and support for complaint handling and troubleshooting by email or through a phone call. On top of that it also offers additional paid training services.

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Verified User

Professional in Information Technology

Telecommunications Company, 1001-5000 employees

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Alternatives Considered

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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Both the tools have similar features and have made it pretty easy to install/deploy/use. Depending on your existing platform (Cloudera vs. Azure) you need to pick the Workbench. Another observation is that Cloudera has better support where you can get feedback on your questions pretty fast (unlike MS). As its a new product, I expect MS to be more efficient in handling customers questions.

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Bharadwaj (Brad) Chivukula

Sr.Technical Manager/Delivery Manager

Nisum Technologies, Inc.Retail, 10,001+ employees

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Return on Investment

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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Paid off for demonstration purposes.

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Verified User

Professional in Research & Development

Utilities Company, 10,001+ employees

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Pricing Details

General

Free Trial

—

Free/Freemium Version

—

Premium Consulting/Integration Services

—

Entry-level set up fee?

No

General

Free Trial

—

Free/Freemium Version

—

Premium Consulting/Integration Services

—

Entry-level set up fee?

No

Rating Summary

Apache Spark

Data Science Workbench

Apache Spark

Data Science Workbench

Apache Spark

Data Science Workbench

Likelihood to Recommend

Apache Spark

Data Science Workbench

Feature Rating Comparison

Connect to Multiple Data Sources

Extend Existing Data Sources

Automatic Data Format Detection

MDM Integration

Visualization

Interactive Data Analysis

Interactive Data Cleaning and Enrichment

Data Transformations

Data Encryption

Built-in Processors

Multiple Model Development Languages and Tools

Automated Machine Learning

Single platform for multiple model development

Self-Service Model Delivery

Flexible Model Publishing Options

Security, Governance, and Cost Controls

Pros

Apache Spark

Data Science Workbench

Cons

Apache Spark

Data Science Workbench

Usability

Apache Spark

Data Science Workbench

Support Rating

Apache Spark

Data Science Workbench

Alternatives Considered

Apache Spark

Data Science Workbench

Return on Investment

Apache Spark

Data Science Workbench

Pricing Details

General

Free Trial

Free/Freemium Version

Premium Consulting/Integration Services

Entry-level set up fee?

General

Free Trial

Free/Freemium Version

Premium Consulting/Integration Services

Entry-level set up fee?

Rating Summary

Add comparison