Apache Hive Features | Limitations of Hive
1. Objective – Hive Features and Limitations
As we know to process structured data in Hadoop, we use Hive. Apart from it, there are several features of Apache Hive. well, it also has several limitations. So, in this Hive Tutorial, we will see “Apache Hive features and limitations of Hive”, we will discuss both features and limitations of Hive. But, before that, we will also learn the introduction of Hive.
2. What is Apache Hive?
Basically, the tool to process structured data in Hadoop we use Hive. It is a data warehouse infrastructure. Moreover, to summarize Big Data, it resides on top of Hadoop. Also, makes querying and analyzing easy.
However, the Apache Software Foundation took it up, but initially, Hive was developed by Facebook. Further Apache Software Foundation developed it as an open source under the name Apache Hive. Although, many different companies use it. Like, Amazon uses it in Amazon Elastic MapReduce.
Follow this link to know more about What is Hive in detail
If these professionals can make a switch to Big Data, so can you:
3. Apache Hive Features and Limitations
a. Hive Features
Some Hive new features are discussed below:
Apache Hive is built on top of Hadoop distributed framework system (HDFS).
ii. Large datasets
However, in distributed storage, it helps to query large datasets residing.
Also, we can say Hive is a distributed data warehouse.
Queries data using a SQL-like language called HiveQL (HQL).
v. Declarative language
HiveQL is a declarative language like SQL.
vi. Table structure
Table structure/s is/are similar to tables in a relational database.
Multiple users can simultaneously query the data using Hive-QL.
viii. Data Analysis
However, to perform more detailed data analysis, Hive allows writing custom MapReduce framework processes.
ix. ETL support
Also, it is possible to extract/transform/load (ETL) Data easily.
x. Data Formats
Moreover, Hive offers the structure on a variety of data formats.
Hive allows access files stored in HDFS. Also, similar others data storage systems such as Apache HBase.
x. Format conversion
Moreover, it allows converting the variety of format from to within Hive. Although, it is very simple and possible.
Follow this link to know about Hive architecture & Components in detail.
b. Limitations of Hive
i. OLTP Processing issues
However, Hive is not designed for Online transaction processing (OLTP). Although, we can use it for the Online Analytical Processing (OLAP).
ii. No Updates
It does not support updates and deletes, however, it does support overwriting or apprehending data.
Basically, in Hive, Subqueries are not supported.
Read more about Hive Operators & Hive Data Types in detail
So, this was all in Features of Hive. Hope you like our explanation.