Top Rated Apache Tez Alternatives
The best thing I like about the Tez is that it can process the enormous quantity of data. It also improves the performance of data processing and always concern with movement of data. Review collected by and hosted on G2.com.
Sometime when we configure Tez as Hive engine sometimes engine can lead to some issues when running in spark jobs. This might be sound some not effective at the particular time. Review collected by and hosted on G2.com.
16 out of 17 Total Reviews for Apache Tez
I and my teammates were used the Apache Tez tool to process a huge amount of data in data in multiple formats in multiple formats like. XLS, XLSX and many more. As a Data Science company, my organization needed this tool at any cost to process data fast in multiple file type formats. Now at my organization, we all data and digital marketing people are using this awesome tool. Review collected by and hosted on G2.com.
While doing the data process work times the tool got stuck to process data, in this case, we are running our query multiple times to process data. The developer team must have to improve this. The User Interface is looking a little dull, It must have to improve and change as look more attractive. Review collected by and hosted on G2.com.
The tool Apache Tez can process a bunch of data at a time in a different format. The data processing time is very less compared to other tools. Apart from the data processing the framework designing tool i most liked about Apache Tez. Review collected by and hosted on G2.com.
Apache Tez does not support every kind of Data analysis-related tool like Hadoop technologies for data processing. The admin team must have to work on this and they must have to resolve these issues from the admin team. Review collected by and hosted on G2.com.
The data processing techniques that Tez is giving is one of the thing that I like most. Running the complex tasks with dynamic physical data flow is the main thing. Review collected by and hosted on G2.com.
While the Apache tez is faster in data processing but it is not considered as the backbone of Hadoop technology. There are some Scenerios where the Tez will not fit well Review collected by and hosted on G2.com.
I like the Tez's ability to process large data sets very quickly.
Its extensibility helps to write optimized data processing apps.
WebUI is also straightforward to use. Review collected by and hosted on G2.com.
The installation process was not very straightforward. The documentation was also very lacking in depth. Review collected by and hosted on G2.com.
We can use the Tez engine in both Hives as well as PIG. Also, the processing speed is much faster than the hive Map-reduce engine. Review collected by and hosted on G2.com.
As compared to other engines which are used to process big data Tez is more scalable and has better performance and throughput. Review collected by and hosted on G2.com.
Fast processing and results on top of big data.
Less io as compared to Hive Map reduce which increases query speed Review collected by and hosted on G2.com.
No concept of caching data as available in spark.Udfs are supported only in java Review collected by and hosted on G2.com.
By using Apache Tez we could integrate multiple data sources collected on third parties applications, effectively improving the processs by reducing time and work prviously dedicated to this activity. Review collected by and hosted on G2.com.
The implementation of Apache Tez with specific regards to the integration of all the applications that we needed to include in the project as sources of the data, required 5 months of analysis, study and set-up of the project. The results though were very effective. Review collected by and hosted on G2.com.
Best for fastest building an application framework which allows for a complex directed-acyclic-graph of tasks for processing data. The data flow is really expressive with proper Api defination. Review collected by and hosted on G2.com.
The association with different third party data aggregation tool is not great and the threads don't utilise the whole efficiency of the system. The customization to data defination can also be improved. Review collected by and hosted on G2.com.
