A company has a lot of data in many disparate sources such as Hive, Cassandra, Redis, and MongoDB.
The company wants to enable its employee to perform fast queries on these underlying data sources using a standard query language.
Which of the following can be used for this purpose?
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A. B. C. D.Answer - A.
The AWS Documentation mentions the following.
Presto is a fast SQL query engine designed for interactive analytic queries over large datasets from multiple sources.
The other components don't have the ability to query multiple data sources.
For more information on Presto, please visit the url.
https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-presto.htmlTo enable employees to perform fast queries on different data sources, the company needs a solution that can unify the data and allow employees to use a standard query language. Among the given options, Presto is the most suitable choice for this purpose.
Presto is an open-source distributed SQL query engine that can connect to various data sources such as Hive, Cassandra, Redis, MongoDB, and more. It allows users to run SQL queries on different data sources simultaneously and provides a unified view of the data. With Presto, employees can use a standard query language (SQL) to access data from different sources, without the need to learn different query languages for each source.
SparkSQL, Hive, and Oozie are also distributed query engines, but they are primarily designed for querying data stored in Hadoop Distributed File System (HDFS) or Apache HBase. While they can also connect to other data sources, they may not provide the same level of flexibility and performance as Presto, especially when dealing with large and diverse data sets.
Therefore, Presto is the best choice for a company that needs to perform fast queries on disparate data sources using a standard query language.