5 HBase Vs. RDBMS Top Functional Differences

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Here're the differences between RDBMS and HBase. HBase in the Big data context has a lot of benefits over RDBMS. The listed differences below make it understandable why HBASE is popular in Hadoop (or Bigdata) platform.  5 HBase Vs. RDBMS Top Functional Differences Here're the differences unlock now. Random Accessing HBase handles a large amount of data that is store in a distributed manner in the column-oriented format while RDBMS is systematic storage of a database that cannot support a random manner for accessing the database. Database Rules RDBMS strictly follows Codd's 12 rules with fixed schemas and row-oriented manner of database and also follows ACID properties. HBase follows BASE properties and implements complex queries. Secondary indexes, complex inner and outer joins, count, sum, sort, group, and data of page and table can easily be accessible by RDBMS. Storage From small to medium storage application there is the use of RDBMS that provides the solution with MyS

Python Web data - How to Extract HTML Tags Easily

With BeautifulSoup you can extract HTML and XML tags easily that present in Web data. Here is the best example of how to remove these.


In Python, the prime step of text analytics is cleaning. You can remove HTML tags using BeautifulSoup parser. Check out Python Logic and removing HTML tags. When analyzing web data, consider the below examples for your projects.

Python Ideas to Remove HTML tags
Python Ideas to Remove HTML tags

How I Removed Using BeautifulSoup

  1. Import BeautifulSoup
  2. Python Logic to Remove HTML tags
  3. Before and after executing the code

1. Import BeautifulSoup

import BeautifulSoup from bs4


2. Python BeautifulSoup: How to Remove HTML Tags

from bs4 import BeautifulSoup

soup = BeautifulSoup("<!DOCTYPE html><html><body><h1>My First Heading</h1><p>My first paragraph.</p></body></html>")

text = soup.get_text()

print(text)


3. Before and After Run

Before the run see the below code.


You need to import BeautifulSoup for Text analytics
Before Executing the code


After Run the tags are parsed. The means in the output tags removed.

I have shared Python sample logic on how to remove HTML tags. Also, given the package name you need. It is a useful example for text analytics.
Result after executing the code

Bottom-line of Result

Below are the steps you need for HTML tags parsing:
  1. Reads input HTML data
  2. Removes HTML tags
  3. Prints only text data


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