TrustRadius: an HG Insights company

Apache Hive vs. Azure Cosmos DB vs. PrestoDB (or Presto)

Save this comparison

Save this comparison

Add Product

Recommended Comparisons

    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

    Azure Cosmos DB

    Score9.1 out of 10
    N/AMicrosoft Azure Cosmos DB is Microsoft's Big Data analysis platform. It is a NoSQL database service and is a replacement for the earlier DocumentDB NoSQL database.N/A

    PrestoDB (or Presto)

    Score10 out of 10
    N/APresto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.N/A
    Pricing
    Apache HiveAzure Cosmos DBPrestoDB (or Presto)
    Editions & Modules
    No answers on this topic
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Apache HiveAzure Cosmos DBPrestoDB (or Presto)
    Free Trial
    NoNoNo
    Free/Freemium Version
    NoNoNo
    Premium Consulting/Integration Services
    NoNoNo
    Entry-level Setup FeeNo setup feeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Community Pulse
    Apache HiveAzure Cosmos DBPrestoDB (or Presto)
    Considered Multiple Products
    Apache
    Chose Apache Hive
    One of the major advantages of using Presto or the main reason why people use Presto (Teradata) is due to that fact it can support multiple data sources - which is lacking as in the case of Apache Hive. But still, most people who come from a Structured data-based background …
    Incentivized
    Chose Apache Hive
    We selected Hive because it supports SQL, schema and provides structure on top of hadoop. Having data structured has its benefits, especially if there are thousands of users processing on the same data over and over again. Pig provides the ability to process unstructured data. …
    Incentivized
    Chose Apache Hive
    Presto is slightly less reliable but much faster for interactive querying. These tools would not be replacements for each other, but rather complements.
    Incentivized
    Chose Apache Hive
    Community support and ease of use -not deployment.

    It enables querying and analyzing large amounts of data stored in HDFS, on the petabyte scale. It has a query language called HQL that transforms SQL queries into MapReduce jobs that run on Hadoop, and it is wonderful for the …
    Incentivized
    Chose Apache Hive
    Due to effective queries resolved time and the performance and user-friendly framework compared to other products.
    Incentivized
    Chose Apache Hive
    Hive was one of the first SQL on Hadoop technologies, and it comes bundled with the main Hadoop distributions of HDP and CDH. Since its release, it has gained good improvements, but selecting the right SQL on Hadoop technology requires a good understanding of the strengths and …
    Incentivized
    Microsoft
    No answer on this topic
    Open Source
    Chose PrestoDB (or Presto)
    I think Presto is one of the best solutions out there today at the cutting edge for interactive query analysis. One of the challenges is presto is a niche tool for the interactive query use case and doesn't have the knobs and whistles as much as Spark. In the foreseeable future …
    Incentivized
    Key User Insights
    Would buy again
    95%
    Would buy again
    18 Answers
    No answers on this topic
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    18 Answers
    No answers on this topic
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    19 Answers
    No answers on this topic
    No answers on this topic
    Lived up to sales and marketing promises
    90%
    Lived up to sales and marketing promises
    9 Answers
    No answers on this topic
    No answers on this topic
    Implementation went as expected
    89%
    Implementation went as expected
    17 Answers
    No answers on this topic
    No answers on this topic
    Best Alternatives
    Apache HiveAzure Cosmos DBPrestoDB (or Presto)
    Small Businesses
    No answers on this topic
    No answers on this topic
    Amazon RDS
    Score8.1 out of 10
    Medium-sized Companies
    Cloudera Enterprise Data Hub
    Score9 out of 10
    HBase
    Score7.3 out of 10
    SingleStore
    Score8.2 out of 10
    Enterprises
    Oracle Exadata
    Score9.8 out of 10
    Cassandra
    Score9 out of 10
    SAP IQ
    Score5.5 out of 10
    All AlternativesView all alternativesView all alternativesView all alternatives
    User Ratings
    Apache HiveAzure Cosmos DBPrestoDB (or Presto)
    Likelihood to Recommend
    8.0
    (35 ratings)
    10.0
    (7 ratings)
    7.8
    (2 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    7.6
    (4 ratings)
    -
    (0 ratings)
    Usability
    8.5
    (7 ratings)
    8.8
    (2 ratings)
    -
    (0 ratings)
    Support Rating
    7.0
    (6 ratings)
    9.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Apache HiveAzure Cosmos DBPrestoDB (or Presto)
    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
    Microsoft
    Like any NoSQL database, whether it's MongoDB or not, it's best suited for unstructured data. It's also well suited for storing raw data before processing it and performing any type of ETL on the data.
    Incentivized
    Read full review
    Open Source
    Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica
    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
    Microsoft
    • Scalable Instantly and automatically serverless database for any large scale business.
    • Quick access and response to data queries due to high speed in reading and writing data
    • Create a powerful digital experience for your customers with real-time offers and agile access to DB with super-fast analysis and comparison for best recommendation
    Incentivized
    Read full review
    Open Source
    • Linking, embedding links and adding images is easy enough.
    • Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
    • Organizing & design is fairly simple with click & drag parameters.
    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
    Microsoft
    • Expensive, so be careful of the use case.
    • We had a thought time migrating from traditional DBs to Cosmos. Azure should provide a seamless platform for the migration of data from on-premises to cloud.
    Incentivized
    Read full review
    Open Source
    • Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
    • Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
    • UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
    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
    Microsoft
    It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.
    Incentivized
    Read full review
    Open Source
    No answers on this topic
    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
    Microsoft
    It has very good compatibility and adaptability with other APIs and developers can safely create new apps because it is compatible with various tools and can be easily managed and run under the cloud, and in terms of security, it is one of the best of its kind, which is very powerful and excellent.
    Incentivized
    Read full review
    Open Source
    No answers on this topic
    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
    Microsoft
    Microsoft is the best when it comes to after-sales support. They have a well-structured training and knowledge base portal that anyone can use. They are usually quick to respond to cases and are on point for on-call support. I have no complaints from a support standpoint. Pretty happy with the support.
    Incentivized
    Read full review
    Open Source
    No answers on this topic
    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
    Microsoft
    Cosmos DB is unique in the industry as a true multi-model, cloud-native database engine that comes with solutions for geo-redundancy, multi-master writes, (globally!) low latency, and cost-effective hosting built in. I've yet to see anything else that even comes close to the power that Cosmos DB packs into its solution. The simplicity and tooling support are nice bonus features as well.
    Incentivized
    Read full review
    Open Source
    Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
    Incentivized
    Read full review
    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
    Microsoft
    • It's made managing raw data much easier
    • It provides a way to maintain raw data at a low cost
    • It's easy to massage the data
    Incentivized
    Read full review
    Open Source
    • Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
    • Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
    • Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.
    Incentivized
    Read full review
    ScreenShots