Top Reasons Why you have a Bright Future with Apache Hive

When it comes to working with a bulk amount of data as in Big Data, Hadoop plays an important role. Hadoop is a conglomerate of many tools and components that help a data scientist to work efficiently. Apache Hive is one such tool of Hadoop ecosystem that is exclusively used for open source data warehousing.  It performs querying and analyzing huge sets of data stored in Hadoop with perfect ease.

Future with hive

What can you do with Hive?

Hive is a server-side deployable tool that supports structured data and has a JDBC and BI integration. It is a query language like SQL and is used for data analysis and report creation. It is a data warehousing tool that is built on the top of the Hadoop Distributed File System (HDFS).

It is designed to perform key functions of data warehousing that include encapsulation of data, working and analysis of huge datasets, and handling ad-hoc queries. With Hive, it is possible to create work with structured data stored in tables. You can manage and query such data comfortably using Hive.

In case you want to improve, query performance in Hadoop programming, Hive can help. With the help of its directory structures, you can partition data and improve query performance.

Where can you use Hive?

  • You can use Hive in data analysis jobs where you have to work with batch jobs, but not weblog data or append-only data.
  • If you are working with Map Reduce, you must have noticed that it does not have optimization and usability. In such cases, you can choose the Hive.
  • A beginner learning to work with databases can choose Hive SQL first. This is because the Hive does not have the complexity that is present in Map Reduce. This makes Hive a beginner friendly tool too. 
  • Hive suits best in cases where schema design flexibility, data serialization, and de-serialization are needed.
  • Hive is an excellent ETL (Extract, Transform, Load) tool that can be used for data analysis systems which need extensibility and scalability.
  • You can choose Hive when you need to work on any of the following four types of the data format: TEXTFILE, SEQUENCEFILE, ORC and RCFILE (Record Columnar File).

Why you have a bright future with Apache Hive?

  • Corporate companies that are into big data are using Hive to look at the data because they are already established with SQL and data warehouse concepts. 
  • Hadoop offers excellent solutions to Big Data problems, and compared to Apache Pig or MapReduce, the future for Apache Hive is very positive. 
  • Experts see Hive as the future of enterprise data management and as a one-stop solution for all the business intelligence and visualization needs.
  • Besides data scientists, Hive works very well for developers too. It has all the features to code for new data architecture projects and new business applications.
  • Hive is beginner friendly and any software enthusiast with basic knowledge of SQL can learn and get started with Hive programming very easily.
  • Hive is witnessing a great future and has many use cases that are rapidly coming up, which means an amplified scope of opportunities for Hive developers.
  • In India, the average salaries for Hive programmers are around Rs. 8 lakhs, which just gets much better with experience.

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