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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Apache Hive

    Score8 out of 10
    N/AApache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.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
    Apache HiveMongoDB
    Editions & Modules
    No answers on this topic
    Shared
    $0
    per month
    Serverless
    $0.10million reads
    million reads
    Dedicated
    $57
    per month
    Offerings
    Pricing Offerings
    Apache HiveMongoDB
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
    More Pricing Information
    Community Pulse
    Apache HiveMongoDB
    Considered Both Products
    Apache
    No answer on this topic
    MongoDB
    Chose MongoDB
    We selected MongoDB because of the following
    • Ease of deployment
    • Use and provisioning on their cloud
    Incentivized
    Key User Insights
    Would buy again
    95%
    Would buy again
    18 Answers
    100%
    Would buy again
    12 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    18 Answers
    100%
    Delivers good value for the price
    12 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    19 Answers
    100%
    Happy with the feature set
    12 Answers
    Lived up to sales and marketing promises
    90%
    Lived up to sales and marketing promises
    9 Answers
    100%
    Lived up to sales and marketing promises
    9 Answers
    Implementation went as expected
    89%
    Implementation went as expected
    17 Answers
    100%
    Implementation went as expected
    12 Answers
    Features
    Apache HiveMongoDB
    NoSQL Databases
    Comparison of NoSQL Databases features of Apache Hive and MongoDB
    Feature
    Apache Hive
    -
    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
    Apache HiveMongoDB
    Small Businesses
    No answers on this topic
    IBM Cloudant
    Score7.4 out of 10
    Medium-sized Companies
    Cloudera Enterprise Data Hub
    Score9 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Enterprises
    Oracle Exadata
    Score9.8 out of 10
    IBM Cloudant
    Score7.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Apache HiveMongoDB
    Likelihood to Recommend
    8.0
    (35 ratings)
    10.0
    (79 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    10.0
    (67 ratings)
    Usability
    8.5
    (7 ratings)
    10.0
    (15 ratings)
    Availability
    -
    (0 ratings)
    9.0
    (1 ratings)
    Support Rating
    7.0
    (6 ratings)
    9.6
    (13 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.4
    (2 ratings)
    User Testimonials
    Apache HiveMongoDB
    Likelihood to Recommend
    Apache
    Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.
    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
    Read full review
    Pros
    Apache
    • Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax.
    • Relatively easy to set up and start using.
    • Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved.
    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
    Apache
    • Some queries, particularly complex joins, are still quite slow and can take hours
    • Previous jobs and queries are not stored sometimes
    • Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond).
    • Sometimes, directories and tables don't load properly which causes confusion
    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
    Apache
    Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
    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
    Apache
    Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.
    Incentivized
    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
    Apache
    Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.
    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
    Apache
    No answers on this topic
    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
    Read full review
    Alternatives Considered
    Apache
    Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
    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.
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    Return on Investment
    Apache
    • Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
    • Apache hive can handle and process large amount of data in a sufficient time manner.
    • It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.
    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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