Likelihood to Recommend We are running it to perform preparation which takes a few hours on EC2 to be running on a spark-based EMR cluster to total the preparation inside minutes rather than a few hours. Ease of utilization and capacity to select from either Hadoop or spark. Processing time diminishes from 5-8 hours to 25-30 minutes compared with the Ec2 occurrence and more in a few cases.
Read full review Heroku is very well suited for startups looking to get a server stack up and running quickly. There is little to no overhead when managing your instances. However, you'll need a background in basic DevOps or system management to make sure everything is set up correctly. In addition, it's easy to accidentally go crazy on pricing. Make sure you're only creating the server instances you need to run the base application and set up an auto-scaler plugin to handle peaks.
Read full review 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. Read full review Heroku has a very simple deployment model, making it easy to get your application up-and-running with minimal effort. We can focus on our efforts the unique aspects of our application. The robust add-on marketplace makes it easy to try out new approaches with minimal effort and investment -- and when we settle on a solution, we can easily scale it. Heroku's support is quite good -- their staff is quite technical and willing to get into the weeds to diagnose even complicated problems. Read full review Cons Sometimes bootstrapping certain tools comes with debugging costs. The tools provided by some of the enterprise editions are great compared to EMR. Like some of the enterprise editions EMR does not provide on premises options. No UI client for saving the workbooks or code snippets. Everything has to go through submitting process. Not really convenient for tracking the job as well. Read full review Large price jumps between certain resource tiers (2x Dyno for $50 per month versus Performance Dyno for $250). Free Postgres next jumps to $50 per month. Marketing/Branding to non-technical stakeholders. As the years pass, I've had to fight more to convince stakeholders on the value of Heroku over AWS. Improve Buildpack documentation. This is one area where Heroku's documentation is fairly confusing. Read full review Likelihood to Renew Heroku is easy to use, services a ton of functions for you out of the box, and provides a means to get a software product off the ground and managed quickly and easily. The tools provide allows a small to medium size org to move very quickly. The CLI tools provided make managing an entire technical infrastructure simple.
Read full review Usability I give Amazon EMR this rating because while it is great at simplifying running big data frameworks, providing the Amazon EMR highlights, product details, and pricing information, and analyzing vast amounts of data, it can be run slow, freeze and glitch sometimes. So overall Amazon EMR is pretty good to use other than some basic issues.
Read full review Easy to use web based console and easy to use command line tools; deployment is done directly from a GIT repository. What more could you ask for? The one thing that keeps me from giving it a 10 is that custom build packs are almost incomprehensible. We used one for a while because we needed cairo graphics processing. Fortunately, I was able to figure out a different way to do what we needed so that we could get off the custom build pack.
Read full review Reliability and Availability Heroku availability correlates pretty strongly to AWS US EAST availability. We had a couple of times where there was a Heroku-specific issue but not for the last 7-8 months.
Read full review Performance The only issue that I ever have is that about 1 out of 20 deployments (git push) will hang and need to be cancelled and done again.
Read full review Support Rating There's a vast group of trained and certified (by AWS) professionals ready to work for anyone that needs to implement, configure or fix EMR. There's also a great amount of documentation that is accessible to anyone who's trying to learn this. And there's also always the help of AWS itself. They have people ready to help you analyze your needs and then make a recommendation.
Read full review I've used it for many years without facing any major problem. It's not hard at all to get used to it, it's documentation is outstanding and simple. We are close to 2020 and I don't think most of the existing companies or startups should still face old problems such as wasting time deploying code and calculate computing resources.
Read full review Implementation Rating Be ready to pay a bit more than expected in the beginning if you're migrating from a big server. The application is probably not ready for the change and you have to keep improving it with time.
It's also important to consider that you can't save anything to the disc as it will be lost when your application restarts, so you have to think about using something like S3.
Read full review Alternatives Considered Snowflake is a lot easier to get started with than the other options.
Snowflake 's data lake building capabilities are far more powerful. Although Amazon EMR isn't our first pick, we've had an excellent experience with EC2 and S3. Because of our current API interfaces, it made more sense for us to continue with Hadoop rather than explore other options.
Read full review Heroku is the more expensive option for hosting compared to some of the cloud platforms we investigated, but it's worth it for us because of the plug-and-play nature of Heroku deployment. We can be up and running in a few minutes and know with precision how much it will cost us each month to run the application, unlike
Amazon Web Services where you have to go to great pains to configure it correctly or else you might end up with a shocking monthly bill. Overall, spending the time to configure
Amazon Web Services or one of its competitors is likely the more affordable and powerful choice, because you have control over so many specifics of the configuration. But it also requires the burden of continuing to maintain and update your AWS instance, whereas with Heroku they take care of security fixes and platform upgrades. It's a great service and we are happy to pay the extra cost for the value-adds Heroku provides.
Read full review Return on Investment Positive: Helped process the jobs amazingly fast. Positive: Did not have to spend much time to learn the system, therefore, saving valuable research time. Negative: Not flexible for some scenarios, like when some plugins are required, or when the project has to be moved in-house. Read full review It has been critical in seamlessly operating our platform with runs all of our programs. It has been impressive with its ability to scale quickly which results in the growth of our work. It allows for tracking of different features which allows for quick problem solving which saves us time. Emily Cooper Director, Illinois Science & Technology Coalition
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