What users are saying about

Apache Spark

99 Ratings

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Top Rated
223 Ratings

Apache Spark

99 Ratings
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Score 8.6 out of 101

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Top Rated
223 Ratings
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Score 8.1 out of 101

Add comparison

Likelihood to Recommend

Apache Spark

Spark is great as a workflow process and extract transform layer process tool. Is really good for machine learning especially for large datasets that can be processed in split file paralallelization. Spark streaming is scalable for close to real-time data workflow process.what it's not good for, is smaller subset of data processing.
Anson Abraham profile photo

MongoDB

Mongo DB is better placed in large projects, with great scalability. It also allows you to work quite comfortably with projects based on programming languages such as javascript angular typescript C #. I believe that its performance is much better with the type of technologies that handle very logical, similar terms of programming. If we use languages like java php, for example, it is better to work with relational databases like postgres or mySql. Since this type of technology allows you to work better with database management frameworks much more agile for these environments, such as JPA, HIBERNATE, Oracle, I think they are much better with this type of architecture and programming languages.
Ronald Melendez profile photo

Feature Rating Comparison

NoSQL Databases

Apache Spark
MongoDB
8.6
Performance
Apache Spark
MongoDB
8.7
Availability
Apache Spark
MongoDB
8.7
Concurrency
Apache Spark
MongoDB
8.3
Security
Apache Spark
MongoDB
8.2
Scalability
Apache Spark
MongoDB
8.7
Data model flexibility
Apache Spark
MongoDB
9.0
Deployment model flexibility
Apache Spark
MongoDB
9.0

Pros

  • Ease of use, the Spark API allows for minimal boilerplate and can be written in a variety of languages including Python, Scala, and Java.
  • Performance, for most applications we have found that jobs are more performant running via Spark than other distributed processing technologies like Map-Reduce, Hive, and Pig.
  • Flexibility, the frameworks comes with support for streaming, batch processing, sql queries, machine learning, etc. It can be used in a variety of applications without needing to integrate a lot of other distributed processing technologies.
No photo available
  • Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
  • Fast performance.
  • It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
  • There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
  • Query syntax is pretty simple to grasp and utilize.
  • Aggregate functions are powerful.
  • Scaling options.
  • Documentation is quite good and versioned for each release.
Joshua Weaver profile photo

Cons

  • Increase the information and trainings that come with the application, especially for debugging since the process is difficult to understand.
  • It should be more attentive to users and make tutorials, to reduce the learning curve.
  • There should be more grouping algorithms.
Carla Borges profile photo
  • When working with large data sets that benefit from many indexes (reads), it can slow down writes.
  • MongoDB is simple to use, but deceptively difficult to master for performance. More documentation around some pitfalls would be great (though there is some and more than there once was, it is improving).
  • MongoDB now has V8, but still runs many operations in a single-threaded capacity. It could be faster for certain tasks.
  • Depending on what's going on, replication lag can be slow and can cause problems.
Tom Maiaroto profile photo

Likelihood to Renew

No score
No answers yet
No answers on this topic
MongoDB8.6
Based on 45 answers
This is a very convenient "go to" database for application CRUD operations. So many applications need to create, read, update, and delete records. Here's the trick though - as a product changes, the data does as well. Having a database that makes this process easy and avoids the need to manage a schema and migrations is extremely valuable.MongoDB may not be the tool for every need but it is often always a tool that gets used for some need or another.
Tom Maiaroto profile photo

Usability

No score
No answers yet
No answers on this topic
MongoDB8.0
Based on 3 answers
It's a great document nosql database, i think
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Support

No score
No answers yet
No answers on this topic
MongoDB8.0
Based on 2 answers
I never had problems with the application. It complies with all the characteristics that the company specifies with this product.
Fernando Malave profile photo

Implementation

No score
No answers yet
No answers on this topic
MongoDB8.4
Based on 2 answers
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
Tom Maiaroto profile photo

Alternatives Considered

I prefer Apache Spark compared to Hadoop, since in my experience Spark has more usability and comes equipped with simple APIs for Scala, Python, Java and Spark SQL, as well as provides feedback in REPL format on the commands. At the same time, Apache Spark seems to have the best performance in the processing of large data that works in memory and, therefore, more processes can be downloaded on Spark than on Hadoop, despite the fact that Hadoop is also a very useful tool.
Carla Borges profile photo
MongoDB was the most full-featured NoSQL database we evaluated - that offered atomic transactions at a document level, built-in HA & DR, open source, robust queries, and enterprise level support.Other platforms had specific parts of what we were looking for - MongoDB had it all.
Jeff Sherard profile photo

Return on Investment

  • Apache Spark has faster performance compared to MapReduce.
  • Combination of Python & Spark is the best. Shorter code, faster and efficient performance.
  • Can replace RDBMS
Kartik Chavan profile photo
  • Faster development of new product features.
  • Cheaper cost of ownership (it's open-source, no licensing fees, easy to host).
Tom Maiaroto profile photo

Screenshots

Apache Spark

Pricing Details

Apache Spark

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

MongoDB

General
Free Trial
Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details