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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    AWS Elastic Beanstalk

    Score8.6 out of 10
    N/AAWS Elastic Beanstalk is the platform-as-a-service offering provided by Amazon and designed to leverage AWS services such as Amazon Elastic Cloud Compute (Amazon EC2), Amazon Simple Storage Service (Amazon S3).

    $35

    per month

    Elasticsearch

    Score8.5 out of 10
    N/AElasticsearch is an enterprise search tool from Elastic in Mountain View, California.

    $16

    per month

    Pricing
    AWS Elastic BeanstalkElasticsearch
    Editions & Modules
    No Charge
    $0
    Users pay for AWS resources (e.g. EC2, S3 buckets, etc.) used to store and run the application.
    Standard
    $16.00
    per month
    Gold
    $19.00
    per month
    Platinum
    $22.00
    per month
    Enterprise
    Contact Sales
    Offerings
    Pricing Offerings
    AWS Elastic BeanstalkElasticsearch
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    AWS Elastic BeanstalkElasticsearch
    Considered Both Products
    Amazon AWS
    No answer on this topic
    Elastic
    Chose Elasticsearch
    All database systems have things they are good at, and things they aren't as good at. Riak/SOLR is great as a K/V store, but SOLR cannot handle requests as fast as ElasticSearch. In fact, SOLR is the reason we had to migrate to ElasticSearch.
    Redis is great at SET operations …
    Incentivized
    Key User Insights
    Would buy again
    88%
    Would buy again
    7 Answers
    82%
    Would buy again
    14 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    8 Answers
    100%
    Delivers good value for the price
    16 Answers
    Happy with the feature set
    88%
    Happy with the feature set
    7 Answers
    100%
    Happy with the feature set
    17 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    5 Answers
    100%
    Lived up to sales and marketing promises
    13 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    7 Answers
    87%
    Implementation went as expected
    13 Answers
    Features
    AWS Elastic BeanstalkElasticsearch
    Platform-as-a-Service
    Comparison of Platform-as-a-Service features of AWS Elastic Beanstalk and Elasticsearch
    Feature
    AWS Elastic Beanstalk
    7.8
    28 Ratings
    1% above category average
    Elasticsearch
    -
    Ratings
    Ease of building user interfaces8.018 Ratings00 Ratings
    Scalability7.028 Ratings00 Ratings
    Platform management overhead8.027 Ratings00 Ratings
    Workflow engine capability7.022 Ratings00 Ratings
    Platform access control8.027 Ratings00 Ratings
    Services-enabled integration8.027 Ratings00 Ratings
    Development environment creation7.027 Ratings00 Ratings
    Development environment replication8.028 Ratings00 Ratings
    Issue monitoring and notification8.027 Ratings00 Ratings
    Issue recovery9.025 Ratings00 Ratings
    Upgrades and platform fixes8.026 Ratings00 Ratings
    Best Alternatives
    AWS Elastic BeanstalkElasticsearch
    Small Businesses
    IBM Cloud Foundry
    Score8.5 out of 10
    Apache Solr
    Score7.9 out of 10
    Medium-sized Companies
    IBM Cloud Private
    Score9.6 out of 10
    IBM Watson Discovery
    Score9 out of 10
    Enterprises
    Red Hat OpenShift
    Score9.1 out of 10
    Amazon CloudSearch
    Score8.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    AWS Elastic BeanstalkElasticsearch
    Likelihood to Recommend
    7.0
    (28 ratings)
    9.0
    (48 ratings)
    Likelihood to Renew
    7.9
    (2 ratings)
    10.0
    (1 ratings)
    Usability
    7.0
    (10 ratings)
    10.0
    (1 ratings)
    Support Rating
    8.0
    (12 ratings)
    7.8
    (9 ratings)
    Implementation Rating
    7.0
    (2 ratings)
    9.0
    (1 ratings)
    User Testimonials
    AWS Elastic BeanstalkElasticsearch
    Likelihood to Recommend
    Amazon AWS
    I have been using AWS Elastic Beanstalk for more than 5 years, and it has made our life so easy and hassle-free. Here are some scenarios where it excels -
    • I have been using different AWS services like EC2, S3, Cloudfront, Serverless, etc. And Elastic Beanstalk makes our lives easier by tieing each service together and making the deployment a smooth process.
    • N number of integrations with different CI/CD pipelines make this most engineer's favourite service.
    • Scalability & Security comes with the service, which makes it the absolute perfect product for your business.
    Personally, I haven't found any situations where it's not appropriate for the use cases it can be used. The pricing is also very cost-effective.
    Incentivized
    Read full review
    Elastic
    Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
    Incentivized
    Read full review
    Pros
    Amazon AWS
    • Getting a project set up using the console or CLI is easy compared to other [computing] platforms.
    • AWS Elastic Beanstalk supports a variety of programming languages so teams can experiment with different frameworks but still use the same compute platform for rapid prototyping.
    • Common application architectures can be referenced as patterns during project [setup].
    • Multiple environments can be deployed for an application giving more flexibility for experimentation.
    Incentivized
    Read full review
    Elastic
    • As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
    • Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
    • Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
    Incentivized
    Read full review
    Cons
    Amazon AWS
    • Limited to the frameworks and configurations that AWS supports. There is no native way to use Elastic Beanstalk to deploy a Go application behind Nginx, for example.
    • It's not always clear what's changed on an underlying system when AWS updates an EB stack; the new version is announced, but AWS does not say what specifically changed in the underlying configuration. This can have unintended consequences and result in additional work in order to figure out what changes were made.
    Incentivized
    Read full review
    Elastic
    • Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
    • Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
    • Schema changes require complete reindexing of an index
    Incentivized
    Read full review
    Likelihood to Renew
    Amazon AWS
    As our technology grows, it makes more sense to individually provision each server rather than have it done via beanstalk. There are several reasons to do so, which I cannot explain without further diving into the architecture itself, but I can tell you this. With automation, you also loose the flexibility to morph the system for your specific needs. So if you expect that in future you need more customization to your deployment process, then there is a good chance that you might try to do things individually rather than use an automation like beanstalk.
    Incentivized
    Read full review
    Elastic
    We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
    Incentivized
    Read full review
    Usability
    Amazon AWS
    The overall usability is good enough, as far as the scaling, interactive UI and logging system is concerned, could do a lot better when it comes to the efficiency, in case of complicated node logics and complicated node architectures. It can have better software compatibility and can try to support collaboration with more softwares
    Incentivized
    Read full review
    Elastic
    To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
    Incentivized
    Read full review
    Support Rating
    Amazon AWS
    As I described earlier it has been really cost effective and really easy for fellow developers who don't want to waste weeks and weeks into learning and manually deploying stuff which basically takes month to create and go live with the Minimal viable product (MVP). With AWS Beanstalk within a week a developer can go live with the Minimal viable product easily.
    Incentivized
    Read full review
    Elastic
    We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
    Incentivized
    Read full review
    Implementation Rating
    Amazon AWS
    - Do as many experiments as you can before you commit on using beanstalk or other AWS features. - Keep future state in mind. Think through what comes next, and if that is technically possible to do so. - Always factor in cost in terms of scaling. - We learned a valuable lesson when we wanted to go multi-region, because then we realized many things needs to change in code. So if you plan on using this a lot, factor multiple regions.
    Incentivized
    Read full review
    Elastic
    Do not mix data and master roles. Dedicate at least 3 nodes just for Master
    Incentivized
    Read full review
    Alternatives Considered
    Amazon AWS
    We also use Heroku and it is a great platform for smaller projects and light Node.js services, but we have found that in terms of cost, the Elastic Beanstalk option is more affordable for the projects that we undertake. The fact that it sits inside of the greater AWS Cloud offering also compels us to use it, since integration is simpler. We have also evaluated Microsoft Azure and gave up trying to get an extremely basic implementation up and running after a few days of struggling with its mediocre user interface and constant issues with documentation being outdated. The authentication model is also badly broken and trying to manage resources is a pain. One cannot compare Azure with anything that Amazon has created in the cloud space since Azure really isn't a mature platform and we are always left wanting when we have to interface with it.
    Incentivized
    Read full review
    Elastic
    As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
    Incentivized
    Read full review
    Return on Investment
    Amazon AWS
    • till now we had not Calculated ROI as the project is still evolving and we had to keep on changing the environment implementation
    • it meets our purpose of quick deployment as compared to on-premises deployment
    • till now we look good as we also controlled our expenses which increased suddenly in the middle of deployment activity
    Incentivized
    Read full review
    Elastic
    • We have had great luck with implementing Elasticsearch for our search and analytics use cases.
    • While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
    • We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
    Incentivized
    Read full review
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