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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Elasticsearch

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

    $16

    per month

    MongoDB Atlas

    Score7.8 out of 10
    N/AMongoDB Atlas is the company's automated managed cloud service, supplying automated deployment, provisioning and patching, and other features supporting database monitoring and optimization.

    $57

    per month

    Pricing
    ElasticsearchMongoDB Atlas
    Editions & Modules
    Standard
    $16.00
    per month
    Gold
    $19.00
    per month
    Platinum
    $22.00
    per month
    Enterprise
    Contact Sales
    Dedicated Clusters
    $57
    per month
    Dedicated Multi-Reigon Clusters
    $95
    per month
    Shared Clusters
    Free
    Offerings
    Pricing Offerings
    ElasticsearchMongoDB Atlas
    Free Trial
    NoNo
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    ElasticsearchMongoDB Atlas
    Considered Both Products
    Elastic
    No answer on this topic
    MongoDB
    Chose MongoDB Atlas
    In general, they all compete against each other, and each solution has its own advantages and disadvantages. While MongoDB Atlas was the way to go for some cases, however, other databases were more fit for some services that MongoDB Atlas, especially if they were managed by us, …
    Incentivized
    Key User Insights
    Would buy again
    82%
    Would buy again
    14 Answers
    100%
    Would buy again
    5 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    100%
    Delivers good value for the price
    5 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    17 Answers
    100%
    Happy with the feature set
    5 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    13 Answers
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    87%
    Implementation went as expected
    13 Answers
    100%
    Implementation went as expected
    5 Answers
    Features
    ElasticsearchMongoDB Atlas
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Elasticsearch and MongoDB Atlas
    Feature
    Elasticsearch
    -
    Ratings
    MongoDB Atlas
    8.9
    6 Ratings
    5% above category average
    Automatic software patching00 Ratings9.16 Ratings
    Database scalability00 Ratings9.96 Ratings
    Automated backups00 Ratings9.96 Ratings
    Database security provisions00 Ratings9.16 Ratings
    Monitoring and metrics00 Ratings6.56 Ratings
    Automatic host deployment00 Ratings9.05 Ratings
    Best Alternatives
    ElasticsearchMongoDB Atlas
    Small Businesses
    Apache Solr
    Score7.9 out of 10
    Google BigQuery
    Score8.8 out of 10
    Medium-sized Companies
    IBM Watson Discovery
    Score9 out of 10
    Azure Database
    Score8.8 out of 10
    Enterprises
    Amazon CloudSearch
    Score8.5 out of 10
    Google Cloud SQL
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    ElasticsearchMongoDB Atlas
    Likelihood to Recommend
    9.0
    (48 ratings)
    8.3
    (6 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    -
    (0 ratings)
    Usability
    10.0
    (1 ratings)
    8.0
    (1 ratings)
    Support Rating
    7.8
    (9 ratings)
    10.0
    (2 ratings)
    Implementation Rating
    9.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    ElasticsearchMongoDB Atlas
    Likelihood to Recommend
    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
    MongoDB
    It is good if you: 1. Have unstructured data that you need to save (since it is NoSQL DB) 2. You don't have time or knowledge to setup the MongoDB Atlas, the managed service is the way to go (Atlas) 3. If you need a multi regional DB across the world
    Incentivized
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    Pros
    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
    MongoDB
    • Generous free and trial plan for evaluation or test purposes.
    • New versions of MongoDB are able to be deployed with Atlas as soon as they're released—deploying recent versions to other services can be difficult or risky.
    • As the key supporters of the open source MongoDB project, the service runs in a highly optimized and performant manner, making it much easier than having to do the work internally.
    Incentivized
    Read full review
    Cons
    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
    MongoDB
    • For someone new, it could be challenging using MongoDB Atlas. Some official video tutorials could help a lot
    • Pricing calculation is sometimes misleading and unpredictable, maybe better variables could be used to provide better insights about the cost
    • Since it is a managed service, we have limited control over the instances and some issues we faced we couldn't;'t know about without reaching out to the support and got fixed from their end. So more control over the instance might help
    • The way of managing users and access is somehow confusing. Maybe it could be placed somewhere easy to access
    Incentivized
    Read full review
    Likelihood to Renew
    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
    MongoDB
    No answers on this topic
    Usability
    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
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    MongoDB
    I would give it 8. Good stuff: 1. Easy to use in terms of creating cluster, integrating with Databases, setting up backups and high availability instance, using the monitors they provide to check cluster status, managing users at company level, configure multiple replicas and cross region databases. Things hard to use: 1. roles and permissions at DB level. 2. Calculate expected costs
    Incentivized
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    Support Rating
    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
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    MongoDB
    We love MongoDB support and have great relationship with them. When we decided to go with MongoDB Atlas, they sent a team of 5 to our company to discuss the process of setting up a Mongo cluster and walked us through. when we have questions, we create a ticket and they will respond very quickly
    Incentivized
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    Implementation Rating
    Elastic
    Do not mix data and master roles. Dedicate at least 3 nodes just for Master
    Incentivized
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    MongoDB
    No answers on this topic
    Alternatives Considered
    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
    MongoDB
    MongoDB is a great product but on premise deployments can be slow. So we turned to Atlas. We also looked at Redis Labs and we use Redis as our side cache for app servers. But we love using MongoDB Atlas for cloud deployments, especially for prototyping because we can get started immediately. And the cost is low and easy to justify.
    Incentivized
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    Return on Investment
    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
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    MongoDB
    • Positive - Faster provisioning so we don't have development teams waiting.
    • Positive - Automated backups and server management - eliminates need for dedicated DBAs.
    Incentivized
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