Apache Hadoop vs. MySQL

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.3 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
MySQL
Score 8.3 out of 10
N/A
MySQL is a popular open-source relational and embedded database, now owned by Oracle.N/A
Pricing
Apache HadoopMySQL
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HadoopMySQL
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HadoopMySQL
Considered Both Products
Hadoop
Chose Apache Hadoop
I haven't worked with other Big Data aggregation services like Hadoop. As far as I know, Hadoop is the leading choice in this field with good cause. There is a lot of community support, custom modules, paid consultants, free and paid training. All this makes it an ideal choice …
Chose Apache Hadoop
Hadoop provides storage for large data sets and a powerful processing model to crunch and transform huge amounts of data. It does not assume the underlying hardware or infrastructure and enables the users to build data processing infrastructure from commodity hardware. All the …
MySQL
Chose MySQL
I have the most experience with MySQL so I feel most comfortable using and implementing it. I like it over MSSQL just because I'm not a fan of some of the features MSSQL has. My Mongo and Hadoop experience was for a very specific purpose and they better matches the project …
Chose MySQL
For reliability and ease of use mySql is better. When the data volume gets larger Hadoop is a faster and more reliable option.
Top Pros
Top Cons
Best Alternatives
Apache HadoopMySQL
Small Businesses

No answers on this topic

Redis™*
Redis™*
Score 9.0 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Redis™*
Redis™*
Score 9.0 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
Redis™*
Redis™*
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopMySQL
Likelihood to Recommend
8.9
(36 ratings)
8.2
(134 ratings)
Likelihood to Renew
9.6
(8 ratings)
9.9
(4 ratings)
Usability
8.5
(5 ratings)
10.0
(6 ratings)
Performance
8.0
(1 ratings)
-
(0 ratings)
Support Rating
7.5
(3 ratings)
8.6
(2 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
Implementation Rating
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Apache HadoopMySQL
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Oracle
From my own perspective and the tasks that I perform on a daily basis, MySQL is perfect. It has a reasonable footprint, is fast enough and offers the security and flexibility I need. Everyone has their preferred applications and, no doubt, for larger data warehouses or more intensive applications, MySQL may have its limits, but for the area that I operate in, it's a great match.
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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Oracle
  • Security: is embedded at each level in MySQL. Authentication mechanisms are in place for configuring user access and even service account access to applications. MySQL is secure enough under the hood to store your sensitive information. Also, additional plugins are available that sit on top of MySQL for even tighter security.
  • Widely adopted: MySQL is used across the industry and is trusted the most. Therefore, if you face any problems, simply Google it and you shall land in plenty of forums. This is a great relief as when you are in a need of help, you can find it right in your browser.
  • Lightweight application: MySQL is not a heavy application. However, the data you store in the database can get heavy with time, but as in the configuration and MySql application files, those are not very heavy and can easily be installed on legacy systems as well.
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Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Oracle
  • Although you can add the data you require as more and more data is added, the fixity of it becomes more critical.
  • As the demand, size, and use of the system increase, you may also need to change or acquire more equipment on your servers, although this is an internal inconvenience for the company.
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Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Oracle
For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.
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Usability
Apache
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
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Oracle
I give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.
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Support Rating
Apache
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
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Oracle
The support staff is friendly, knowledgeable, and efficient. I only had to get part way through my explanations before they had a solution. They will walk you through a fix or actually connect in and fix the problem for you--or would if you can allow it. I've done it both ways with them. They are always forthcoming with 'how to do this if it happens again' information. I love working with MySQL support.
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Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Oracle
No answers on this topic
Implementation Rating
Apache
No answers on this topic
Oracle
1. Estimate your data size. 2. Test, test, and test.
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Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Oracle
MongoDB has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant in the event of a DR or outage.
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Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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Oracle
  • As it is an open source solution through community solution, we can use it in a multitude of projects without cost license
  • The acquisition by Oracle makes you need to contract support for the enterprise version
  • If you have knowledge about oracle databases, you can get more out of the enterprise version
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ScreenShots