Apache Spark vs. MuleSoft Anypoint Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark
Score 8.7 out of 10
N/A
N/AN/A
Anypoint Platform
Score 8.0 out of 10
N/A
The Anypoint Platform developed by MuleSoft and acquired by Salesforce in early 2018 is designed to connect apps, data, and devices anywhere, on-premises or in the cloud. This platform was built to offer out-of-the-box connectors as well as tools that architects and developers can adopt quickly to design, build and manage the entire lifecycle of their APIs, applications, and products.N/A
Pricing
Apache SparkMuleSoft Anypoint Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SparkAnypoint Platform
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache SparkMuleSoft Anypoint Platform
Considered Both Products
Apache Spark

No answer on this topic

Anypoint Platform
Chose MuleSoft Anypoint Platform
It is a powerful tool with smart intelligence. The drag and drop feature makes my work easy. The tool has great connecting support which is the best reason to use the tool on a daily basis. Powerful functionality with designing and implementing APIs. Hosted on public IP.
Top Pros
Top Cons
Features
Apache SparkMuleSoft Anypoint Platform
Cloud Data Integration
Comparison of Cloud Data Integration features of Product A and Product B
Apache Spark
-
Ratings
MuleSoft Anypoint Platform
8.6
10 Ratings
6% above category average
Pre-built connectors00 Ratings8.810 Ratings
Connector modification00 Ratings8.510 Ratings
Support for real-time and batch integration00 Ratings8.510 Ratings
Data quality services00 Ratings8.310 Ratings
Data security features00 Ratings8.510 Ratings
Monitoring console00 Ratings9.010 Ratings
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Apache SparkMuleSoft Anypoint Platform
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IBM Analytics Engine
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User Ratings
Apache SparkMuleSoft Anypoint Platform
Likelihood to Recommend
9.9
(23 ratings)
9.1
(20 ratings)
Likelihood to Renew
10.0
(1 ratings)
9.0
(1 ratings)
Usability
10.0
(3 ratings)
8.0
(1 ratings)
Support Rating
8.7
(4 ratings)
6.8
(4 ratings)
User Testimonials
Apache SparkMuleSoft Anypoint Platform
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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Salesforce
MuleSoft Anypoint Platform is best tool in the market for developing APIs with complex structures communicating with various different types of applications including web applications as well as legacy applications. Also applications including database connectivity for fetching and updating data in the DB tables. I cant think of any scenario which MuleSoft Anypoint Platform could not be used for developing the integrations.
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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
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Salesforce
  • API Manager provides easy API Policy Governance. You do not have to manage multiple platforms for managing the policies.
  • Supports hybrid Mule EBS environments. You can configure both CouldHub-based and on-premise-based API using Mulesoft API manager in a similar manner.
  • It's very easy to implement API proxy.
  • User friendly UI.
  • Single platform to manage all.
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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
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Salesforce
  • Has more features than what we really need so we're paying for more than we use. Sort of like paying for an Abrams tank when all we really need is a Toyota Corolla.
  • Not a value product, tends to be expensive.
  • Takes a while for developers to learn to use Mulesoft Anypoint.
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Likelihood to Renew
Apache
Capacity of computing data in cluster and fast speed.
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Salesforce
No answers on this topic
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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Salesforce
simple and easy graphics and containers helps developers to write complex flows
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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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Salesforce
Anypoint Platform support is very responsive. There is also a huge knowledge base and an active online forum where answers to most questions can be found. When needed support engages the engineering group so adequate solutions or workarounds are always provided.
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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.
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Salesforce
Once we have moved all of our system integration APIs to the MuleSoft Anypoint Platform, we will need to communicate with a wide variety of external systems. All of our business and service logic is stored in the aforementioned core systems. Anypoint Platform (and all of our APIs) makes it easy to connect to various other platforms. In order to link to these many other systems, connectors and/or components are utilized, and they are simple to configure and integrate.
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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
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Salesforce
  • Mulesoft can be used to provide an integration platform to a large number of systems like Salesforce, ODBC, JDBC, SAP, Mongo DB, etc.
  • An excellent option to develop microservices and real-time integrations.
  • Not as robust in handling large data volumes, Informatica is better in that respect.
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ScreenShots

Anypoint Platform Screenshots

Screenshot of Connect any endpoints using out-of-the-box connectors, dynamic connectivity to API specifications, or by building reusable connectors with Anypoint DevKit™.Screenshot of A reporting suite that provides a real-time view of API consumption trends and operational performance. Analytics provides insight into how your API is being used and informs forward-looking design decisions.Screenshot of A platform to engage with API developers and drive adoption. Share documentation, examples and manage developer access from a single platform.