Apache Hive vs. Datameer

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Hive
Score 8.2 out of 10
N/A
Apache 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
Datameer
Score 8.5 out of 10
N/A
Datameer helps businesses clean up, combine, and organize data to make sense of it and use it for reports and machine learning.N/A
Pricing
Apache HiveDatameer
Editions & Modules
No answers on this topic
Team/Enterprise
Contact for pricing
per month Team
Offerings
Pricing Offerings
Apache HiveDatameer
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HiveDatameer
Considered Both Products
Apache Hive

No answer on this topic

Datameer
Chose Datameer
Datameer was not chosen to exclude other tools. Other tools are still used and gaining traction due to their suitability to a task and due to cost-effectiveness of license models. Every organization needs to determine the best approach to the data flow into and out of Hadoop, …
Chose Datameer
I have compared Datameer with the tools listed above and it blows them out of the water. Datameer is much more user friendly than these tools and is also a lot more powerful. Once the Q1 release comes out with drill down capabilities on the infographics, Datameer will surpass …
Top Pros
Top Cons
Best Alternatives
Apache HiveDatameer
Small Businesses
Google BigQuery
Google BigQuery
Score 8.6 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 8.2 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HiveDatameer
Likelihood to Recommend
8.0
(35 ratings)
9.0
(9 ratings)
Likelihood to Renew
10.0
(1 ratings)
6.4
(7 ratings)
Usability
8.5
(7 ratings)
9.0
(1 ratings)
Support Rating
7.0
(6 ratings)
8.0
(1 ratings)
User Testimonials
Apache HiveDatameer
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.
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Datameer
Datameer is a great tool if someone is capable of keeping the most recent version of the tool up to date along with the most recent version of the distribution of Hadoop. The tool is easy to support but it must have someone who can run the back end processes
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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.
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Datameer
  • It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
  • It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
  • Excel feature is awesome for business users which is already provided by Datameer.
  • Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
  • Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
  • It can be used in premise or in a cloud computing environment.
  • Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.
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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
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Datameer
  • Concentration issues are possible while using a lot of tabs at once.
  • In most cases, the length of a tutorial video is excessive.
  • A more condensed design is certainly a viable option.
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Likelihood to Renew
Apache
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
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Datameer
Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel
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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.
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Datameer
Easy to use for most things, starts to require some planning as your projects get more complex.
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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.
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Datameer
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
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Datameer
Pricing, support, and ease of use. We plan to scale up our data over the net few years and Datameer gives us all the things we need in one tool. Handles large transformations quickly and works with all the cloud data warehouses.
Datameer's per-user pricing sealed the deal for us as we plan to transfer much more data over the next few years. We looked at Fivetran but the usage pricing discourages growth. We also looked at Informatica but it was too expensive and didn't work as well with other BI tools like Datameer does.
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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.
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Datameer
  • We have not been able to reach our business objectives just yet.
  • Hadoop its a hard sell in most companies still.
  • Legacy skills are still highly on demand and as long as an easier path leverage SQL for example is available, it would be hard to gain more adoption.
Read full review
ScreenShots

Datameer Screenshots

Screenshot of DATA TRANSFORMATION: SQL or No Code

SQL SELECT statements can be used to explore and shape data. Work is represented visually on a canvas like interface, making it easier to design and maintain projects.

Datameer includes library of pre-built drag-and-drop transformations to accelerate SQL development or transform datasets without writing code.Screenshot of DATA CATALOG: Collaboration in Snowflake

Search, Metadata, Data Profiling, and Auto documentationScreenshot of AUTOMATION & INSIGHTS

Insights can be sent to email or Slack, integrated, and deployed to SnowflakeScreenshot of PRODUCTION PIPELINES: From ad-hoc exploration to production pipelines

GIT version control, materialization, dependency management, monitoring