What are the pros and cons of hive?

Despite these disadvantages, Hive also a host of advantages that its many users love about the software.

• Hive combines the features of other project management software.
• It is versatile.
• Customer support is robust.
• Price is good.
• It has numerous integrations.
• It is flexible.
• Tasks cards are easy to use.

What is the disadvantage of hive?

Apache Hive Limitations Hive does not support update and delete operation on tables. Subqueries are not supported. The latency in the apache hive query is very high. Hive is not used for real-time data querying since it takes a while to produce a result.

How do you think it would be beneficial using hive for big databases?

Hive is meant for huge sets of data. While it might take forever for a small number of rows, if you organize your data well, you can process millions or billions of rows much more quickly than otherwise.

What is hive and its uses?

Hive allows users to read, write, and manage petabytes of data using SQL. Hive is built on top of Apache Hadoop, which is an open-source framework used to efficiently store and process large datasets. As a result, Hive is closely integrated with Hadoop, and is designed to work quickly on petabytes of data.

Is Hive relational database?

No, we cannot call Apache Hive a relational database, as it is a data warehouse which is built on top of Apache Hadoop for providing data summarization, query and, analysis. It supports queries expressed in a language called HiveQL, which automatically translates SQL-like queries into MapReduce jobs executed on Hadoop.

Why is Hive suited for big data?

Understanding Hive big data through the lens of data analytics can help us get more insights into the working of Apache Hive. By using a batch processing sequence, Hive generates data analytics in a much easier and organized form that also requires less time as compared to traditional tools.

What is the primary purpose of hive in the Hadoop architecture?

Hive is an ETL and data warehouse tool on top of Hadoop ecosystem and used for processing structured and semi structured data. Hive is a database present in Hadoop ecosystem performs DDL and DML operations, and it provides flexible query language such as HQL for better querying and processing of data.

Is Hive a good database?

It is well suited for batch processing data like: Log processing, Text mining, Document indexing, Customer-facing business intelligence, Predictive modeling, hypothesis testing etc. Hive is not designed for online transaction processing and does not offer real-time queries.