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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google Cloud AI

    Score8.7 out of 10
    N/AGoogle Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.N/A

    MongoDB

    Score8.8 out of 10
    N/AMongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

    $0.10

    million reads

    Pricing
    Google Cloud AIMongoDB
    Editions & Modules
    No answers on this topic
    Shared
    $0
    per month
    Serverless
    $0.10million reads
    million reads
    Dedicated
    $57
    per month
    Offerings
    Pricing Offerings
    Google Cloud AIMongoDB
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details—Fully managed, global cloud database on AWS, Azure, and GCP
    More Pricing Information
    Community Pulse
    Google Cloud AIMongoDB
    Considered Both Products
    Google
    No answer on this topic
    MongoDB
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    12 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    12 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    12 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    9 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    12 Answers
    Features
    Google Cloud AIMongoDB
    NoSQL Databases
    Comparison of NoSQL Databases features of Google Cloud AI and MongoDB
    Feature
    Google Cloud AI
    -
    Ratings
    MongoDB
    10.0
    39 Ratings
    16% above category average
    Performance00 Ratings10.039 Ratings
    Availability00 Ratings10.039 Ratings
    Concurrency00 Ratings10.039 Ratings
    Security00 Ratings10.039 Ratings
    Scalability00 Ratings10.039 Ratings
    Data model flexibility00 Ratings10.039 Ratings
    Deployment model flexibility00 Ratings10.038 Ratings
    Best Alternatives
    Google Cloud AIMongoDB
    Small Businesses
    TensorFlow
    Score7.6 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Medium-sized Companies
    TensorFlow
    Score7.6 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Enterprises
    TensorFlow
    Score7.6 out of 10
    IBM Cloudant
    Score7.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google Cloud AIMongoDB
    Likelihood to Recommend
    8.0
    (7 ratings)
    10.0
    (79 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    10.0
    (67 ratings)
    Usability
    8.0
    (2 ratings)
    10.0
    (15 ratings)
    Availability
    -
    (0 ratings)
    9.0
    (1 ratings)
    Support Rating
    7.3
    (3 ratings)
    9.6
    (13 ratings)
    Implementation Rating
    10.0
    (1 ratings)
    8.4
    (2 ratings)
    User Testimonials
    Google Cloud AIMongoDB
    Likelihood to Recommend
    Google
    Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
    Incentivized
    Read full review
    MongoDB
    If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
    Incentivized
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    Pros
    Google
    • good conversion from the voice to the text
    • speed in the conversion from voice to text
    • time-saving in the conversion activity
    • analysis of the results of the conversion in real time
    Incentivized
    Read full review
    MongoDB
    • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
    • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
    • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
    Incentivized
    Read full review
    Cons
    Google
    • Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
    • Customization of existing modules and libraries is harder and it does need time and experience to learn.
    • Google Cloud AI can do a better job in providing better support for Python and other coding languages.
    Incentivized
    Read full review
    MongoDB
    • An aggregate pipeline can be a bit overwhelming as a newcomer.
    • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
    • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
    Incentivized
    Read full review
    Likelihood to Renew
    Google
    We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
    Incentivized
    Read full review
    MongoDB
    I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
    Incentivized
    Read full review
    Usability
    Google
    I give 8 because although it´s a tool I really enjoy working with, I think Google Cloud AI's impact is just starting, therefore I can visualize a lot/space of improvements in this tool. As an example the application of AI in international environments with different languages is a good example of that space/room to improve.
    Read full review
    MongoDB
    NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
    Incentivized
    Read full review
    Support Rating
    Google
    Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
    Incentivized
    Read full review
    MongoDB
    Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
    Incentivized
    Read full review
    Implementation Rating
    Google
    In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
    Incentivized
    Read full review
    MongoDB
    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.
    Incentivized
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    Alternatives Considered
    Google
    These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
    Incentivized
    Read full review
    MongoDB
    We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
    Read full review
    Return on Investment
    Google
    • Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
    • We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
    • The ROI seems positive since we are full in with Google, and the tools come along with the functionality.
    Incentivized
    Read full review
    MongoDB
    • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
    • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
    Read full review
    ScreenShots

    MongoDB Screenshots

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