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Score 8.2 out of 101
90 Ratings
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Score 8.5 out of 101

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Likelihood to Recommend

Amazon EMR

Amazon Elastic MapReduce is useful in cases where two conditions are met. First, that you are planning on using multiple big data tools simultaneously to analyze big data sets. And second, that you need a tool that simplifies managing big data tools. If these two conditions are met, MapReduce does a great job. The user interface is simple. The program eliminates some programming requirements. The software also makes setting up big data analyses much easier. With these benefits acknowledged, MapReduce is not a good tool for "small" data analyses, given that there are other tools that do the job quicker and much more professional output. If you're on the fence, try out MapReduce with competing "small" data tools and see if you really need big data software.
Thomas Young profile photo

Amazon Redshift

Redshift is a viable platform to house a large or very large data warehouse designed for performance and scalability. It is especially well-suited in the cases where your source data is already stored inside of the AWS services infrastructure.
Michael Romm profile photo

Pros

  • Amazon Elastic MapReduce works well for managing analyses that use multiple tools, such as Hadoop and Spark. If it were not for the fact that we use multiple tools, there would be less need for MapReduce.
  • MapReduce is always on. I've never had a problem getting data analyses to run on the system. It's simple to set up data mining projects.
  • Amazon Elastic MapReduce has no problems dealing with very large data sets. It processes them just fine. With that said, the outputs don't come instantaneously. It takes time.
Thomas Young profile photo
  • Redshift seems to be as fast processing a large dataset as it is with a small one. It seems, when the dataset size is significantly increased (10x, 100x, 1000x, etc.), DML queries are often executed within the same amount of time.
  • Redshift has a powerful graphical admin tool to monitor the ongoing queries in real time and historically.
  • Easily expandable capacity. Automatic snapshots that eliminate the need for managing backups. Simple database maintenance strategies with the VACUUM and ANALYZE commands.
  • Abundance of detailed documentation and tutorials.
Michael Romm profile photo

Cons

  • The analytical processes generally run quicker with the standalone tools of Hadoop, Spark, and others. If you only use one big data tool and don't really need things simplified, then Elastic MapReduce is more of an overhead tool that doesn't add much value.
  • The analytical capabilities of Elastic MapReduce are nowhere near as complex or broad as non-big data tools. I would suggest not using the tool unless your data really is big data.
  • The machine learning capabilities of Elastic MapReduce (using the big data tools of Hadoop/Spark) are good but are not as easy to use as other machine learning tools.
Thomas Young profile photo
  • Lack of enforced constraints (except NOT NULL column constraints). You have to be very careful in your testing to make sure that you aren't duplicating rows.
  • No stored procedure support. Everything must be accomplished through ETL
  • Write operations are very slow and complex.Native SQL row level INSERT and UPDATE statements take an extremely long time to execute. In order to get around this for external data that needs to be loaded, you have to bulk load the data from a flat file to a stage table, then upsert the data from the stage table to your destination table. For data already present in the database, ELT is the only viable way of transforming the data.
  • No good native data modelling tools.
  • Random nondescript errors happen occasionally. The error messages are not decipherable and forums will have no clues as to what happened. It is just a fact of life.
  • No trigger support.
  • OLTP style queries are painfully slow. Don't even think about using Redshift for OLTP...
Seth Goldberg profile photo

Usability

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Amazon Redshift10.0
Based on 1 answer
Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
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Alternatives Considered

Perhaps the biggest advantage Amazon Elastic MapReduce has over competing big data management software is the user base. Elastic MapReduce, compliments of its connection with Amazon, has a large user base to whom questions about functionality can be addressed. The software also has a very nice user interface. Additionally, Elastic MapReduce runs fairly quickly and the results are generally easier to manipulate. With this said, Elastic MapReduce is definitely not the easiest nor quickest tool for big data analytics.
Thomas Young profile photo
  1. Compared to Oracle Data Warehouse, Redshift is a better data warehouse. However, this comes at a cost of advanced functionality and the ability to do OLTP style processing. What you gain is faster querying time and better scalability.
  2. Compared to MySQL, you gain a WHOLE lot. MySQL is terrible for data warehousing and is still gaining features that other databases have had for years (ie. hash joins).
  3. Compared to Teradata, Redshift is a far cheaper option. This comes at the expense of functionality like partitioning and indexing. For the money though, Redshift is still far better since I personally believe you get much more bang for your buck.
Seth Goldberg profile photo

Return on Investment

  • Amazon Elastic MapReduce has had a positive ROI in the sense that it saved time managing big data projects where analysts were using different big data tools. Essentially, an increase in employee productivity.
  • Elastic MapReduce is not worth it in cases where you're just trying things out. You'll likely lose money unless you're sure that using MapReduce is a good idea.
  • Elastic MapReduce takes some time learning, although not too much. If the employee is less well-versed in big data analytics, the software is a high hill to climb that eats up employee time.
Thomas Young profile photo
  • It provides great returns due to its fast processing data analytics purpose.
  • It sometimes toss for cost of AWS Service with Amazon Redshift.
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Pricing Details

Amazon EMR

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

Amazon Redshift

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