22 Reviews and Ratings
18 Reviews and Ratings
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Apache Pig is best suited for ETL-based data processes. It is good in performance in handling and analyzing a large amount of data. it gives faster results than any other similar tool. It is easy to implement and any user with some initial training or some prior SQL knowledge can work on it. Apache Pig is proud to have a large community base globally.Incentivized
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
Its performance, ease of use, and simplicity in learning and deployment.Using this tool, we can quickly analyze large amounts of data.It's adequate for map-reducing large datasets and fully abstracted MapReduce.Incentivized
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.
UDFS Python errors are not interpretable. Developer struggles for a very very long time if he/she gets these errors.Being in early stage, it still has a small community for help in related matters.It needs a lot of improvements yet. Only recently they added datetime module for time series, which is a very basic requirement.Incentivized
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.Incentivized
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
It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.Incentivized
Easy to use for most things, starts to require some planning as your projects get more complex.
The documentation is adequate. I'm not sure how large of an external community there is for support.Incentivized
Apache Pig might help to start things faster at first and it was one of the best tool years back but it lacks important features that are needed in the data engineering world right now. Pig also has a steeper learning curve since it uses a proprietary language compared to Spark which can be coded with Python, Java. Incentivized
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.
Higher learning curve than other similar technologies so on-boarding new engineers or change ownership of Apache Pig code tends to be a bit of a headacheOnce the language is learned and understood it can be relatively straightforward to write simple Pig scripts so development can go relatively quickly with a skilled teamAs distributed technologies grow and improve, overall Apache Pig feels left in the dust and is more legacy code to support than something to actively develop with.Incentivized
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.Incentivized