By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    AI analytics
    AI-Based Analytics Are Changing the Future of Credit Cards
    6 Min Read
    data overload showing data analytics
    How Does Next-Gen SIEM Prevent Data Overload For Security Analysts?
    8 Min Read
    hire a marketing agency with a background in data analytics
    5 Reasons to Hire a Marketing Agency that Knows Data Analytics
    7 Min Read
    predictive analytics for amazon pricing
    Using Predictive Analytics to Get the Best Deals on Amazon
    8 Min Read
    data science anayst
    Growing Demand for Data Science & Data Analyst Roles
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: Apache Spark and Hadoop: The best big data solution for enterprises
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > Apache Spark and Hadoop: The best big data solution for enterprises
Best PracticesData MiningData WarehousingHadoop

Apache Spark and Hadoop: The best big data solution for enterprises

jagadish
Last updated: 2017/10/23 at 9:10 PM
jagadish
6 Min Read
SHARE

The term big data has become the center of attention for enterprises. In the past, business decisions have been made on the basis of transactional data stored in relational databases. This is known as traditional data, which is in structured form and easy to analyze for getting business insights.

Apart from this critical business data, there is a huge potential treasure stored in the non-traditional and unstructured data which enterprises are continuously producing in the form of weblogs, emails, sensor generated data, and social media channels. This data is only as useful as the decisions it enables. Enterprises are looking for the best data science solution with high speed velocity to capture, process, and analyze the unstructured data in real-time.

56% of Enterprises Will Increase Their Investment in Big Data over the Next Three Years – Forbes

Spark and Hadoop: The big data processing platform for enterprises

More Read

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices

Tips to Protect Office 365 Systems from Data Breaches
CASBs Help Cloud-Based Businesses Avoid Data Breaches
Data Mining Technology Helps Online Brands Optimize Their Branding
Four Strategies For Effective Database Compliance

Hadoop and Spark are both big data frameworks used in the data science projects to extract useful insights. Both the frameworks are not mutually exclusive and they can work together. Hadoop is a parallel data processing platform that uses open source software, a distributed file system (HDFS), and MapReduce to store, manage, and process huge data sets. This is being deployed by the businesses for a long time. Most MapReduce jobs are long running batch jobs which take minutes or hours to complete.

But, now we see relatively less market adoption since Spark is available. It is a useful and reliable platform with flexibility, scalability, and affordability.

Let’s understand the big data first before determining the best framework for big businesses. Big data spans across the three dimensions which are volume, velocity, and variety.

Volume: Big businesses are flooded with ever-growing data of all types easily accumulating terabytes or petabytes of information. Enterprises need a speedy system to analyze this bulky data to process each day. This is where Spark has major advantages over Hadoop as it can process stored as well as streaming data in real-time.

Velocity: The huge amount of data enterprises are receiving needs to process with high velocity as sometimes even a delay of 5 minutes can be too late. For time sensitive processes such as fraud and robbery, the data must be used as it streams into your organization for gaining maximum value. This is where Spark can play a crucial role by processing bulk data with speed.

Variety: Big data consists of structured and unstructured data such as text, audio, video, sensor data, log files, click streams, etc. Useful insights can only be gained after analyzing these data types all-together. To make your business more agile, enterprises need to process all new and emerging data faster. By adopting Spark it is possible to answer all those questions which were previously beyond your reach.

Spark is capable of managing all the big data processing requirements with a variety of datasets. The other advantage of Spark over Hadoop is the relative ease of use and flexibility. With Spark it is possible to capture, store, process, and analyze unstructured data from various sources. Apache Spark is an open source cluster computing framework with in memory processing which can speed up analytical app processing up to100 times faster than the other data processing frameworks available. This is the reason which makes Spark the ultimate choice for the enterprises when speed is their preference.

Spark Ecosystem

Some businesses may not require data processing quickly or in real-time. Also, one must take a note that Spark does not include its own system for organizing files in a distributed style and that’s why it needs a system provided by any third party. It runs everywhere- Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources including Cassandra, HDFS, HBase, and S3. Similarly, Spark has its own machine learning library MLib, whereas a Hadoop system needs a third party machine learning library.

However both frameworks do not perform the same tasks and they are able to work together. Ultimately, we can say that both the data science frameworks can be preferred by enterprises depending on their data processing requirements and values gained from the big data.

By getting armed with the right tools for the right tasks enterprises can ignite a firestorm of activities in the present data scenario to gain competitive advantages by creating values. Also, enterprises can use multiple tools instead of relying on just one.

Let’s prioritize what you want to achieve from big data of your business. Based on your priorities we can come up with the best solution for getting useful insights for your enterprise.

The post Apache Spark and Hadoop: The best big data solution for enterprises appeared first on Softweb Solutions.

jagadish June 1, 2016
Share This Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Best Practices Big Data Data Collection Data Management Privacy
data protection for SMEs
8 Crucial Tips to Help SMEs Guard Against Data Breaches
Data Management
How AI is Boosting the Customer Support Game
How AI is Boosting the Customer Support Game
Artificial Intelligence
AI analytics
AI-Based Analytics Are Changing the Future of Credit Cards
Analytics Artificial Intelligence Exclusive

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices
Best PracticesBig DataData CollectionData ManagementPrivacy

Data Ethics: Safeguarding Privacy and Ensuring Responsible Data Practices

7 Min Read
office 365 data protection
Risk Management

Tips to Protect Office 365 Systems from Data Breaches

9 Min Read
CASB
Security

CASBs Help Cloud-Based Businesses Avoid Data Breaches

6 Min Read
data mining
Data Mining

Data Mining Technology Helps Online Brands Optimize Their Branding

7 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?