Apache Hadoop vs. Apache Hive

Apache Hadoop

268 Reviews and Ratings

Apache Hive

95 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Hadoop	Score7.9 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
Apache Hive	Score8 out of 10	N/A	Apache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.	N/A

Pricing

Hadoop

Apache Hive

No answers on this topic

No answers on this topic

Pricing Offerings
Hadoop	Apache Hive
Free Trial
No	No
Free/Freemium Version
Yes	No
Premium Consulting/Integration Services
No	No

No setup fee

No setup fee

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Community Pulse
Key User Insights
	Hadoop	Apache Hive
Considered Both Products	Apache Kartik Chavan Peer Educator (Tutor) & Supplemental Instructions (SI) Leader in Information Technology at The University of Texas at Arlington (Higher Education, 1001-5000 employees) Chose Hadoop For real-time streaming, use Spark; can provide a stark contrast to the way MR works Hadoop offers a scalable, cost-effective and highly available solution for big data storage and processing. Amazon Redshift is somewhat closer to Hadoop. But to analyze Petabytes of data Hadoop … Incentivized Helpful? Bharadwaj (Brad) Chivukula Sr. Engineering Manager/Delivery Manager in Information Technology at Nisum Technologies, Inc. (Retail, 10,001+ employees) Chose Hadoop For real-time streaming, use Spark; can provide a stark contrast to the way MR works Use Hive for querying purposes Incentivized Helpful? Bhushan Lakhe Senior Vice President in Information Technology at Ipsos (Information Technology and Services, 10,001+ employees) Chose Hadoop not applicable - I have not evaluated any other products Helpful?	Apache Omkar Marne Research Application Software Engineer in Information Technology at University of North Carolina at Charlotte (Higher Education, 1001-5000 employees) Chose Apache Hive Apache Hadoop is built on top of the Hadoop File system so it gives its best when integrated with Hadoop. Data analysis and query optimization become very easy when used with Hadoop to perform Extract transform load operations. As Hadoop is a big data system and handles large … Incentivized Helpful? akshay kashyap CONSULTANT in Information Technology at Deloitte Digital (Consumer Goods, 5001-10,000 employees) Chose Apache Hive Apache Hive is a query language developed by Facebook to query over a large distributed dataset. Apache is a query engine that runs on top of HDFS, so it utilizes the resources of HDFS Hadoop setup, while Apache Spark is an in memory compute engine, and that's why [it is] much … Incentivized Helpful? Verified User Chose Apache Hive To query a huge, distributed dataset, Apache Hive was built by Facebook. Unlike Apache Hive, Apache Spark is an in-memory computation engine, which is why it is significantly quicker than Apache Hive at querying large amounts of data. In contrast to Apache HBase, Apache Hive is … Incentivized Helpful? Verified User Chose Apache Hive Hive and Spark have the same parent company hence they share a lot of common features. Hive follows SQL syntax while Spark has support for RDD, DataFrame API. DataFrame API supports both SQL syntax and has custom functions to perform the same functionality. Spark is faster and … Incentivized Helpful? Nicolas Hubert Machine Learning Engineer in Information Technology at Credit Suisse (Banking, 10,001+ employees) Chose Apache Hive Easy to understand, well supported by the community, good documentation. However, it is possible that SAP Business Warehouse could be a good fit, too, even maybe better. I did not have the chance to try it though. We selected Apache Hive because it was far less expensive and … Incentivized Helpful? Verified User Chose Apache Hive [We selected Apache Hive because] It's from apache and opensource. So it's free. Incentivized Helpful? Tejaswar Rao Associate Consultant in Information Technology at Wipro (Computer Software, 10,001+ employees) Chose Apache Hive Faster response time and also can handle complex analytical queries Can able to write custom function using python and hive Able to connect using hadoop components and also using R Incentivized Helpful? Bharadwaj (Brad) Chivukula Sr.Technical Manager/Delivery Manager in Information Technology at Nisum Technologies, Inc. (Retail, 10,001+ employees) Chose Apache Hive For storing bulk amount of data in a tabular manner, and where there's no need need of primary key, or just in case, if redundant data is received, it will not cause a problem. For small amounts of data, it does run MR, so beware. If your intention is to use it as a … Incentivized Helpful? Verified User Chose Apache Hive Hive is SQL compliant which makes it easy for the data folks compared to Pig Incentivized Helpful? Verified User Chose Apache Hive Apache Pig is probably the most direct technology to compare to Hive and has several different use cases to Hive. If you want to simplify processing tasks that run using MapReduce then Apache Pig may be a better tool for the job. However if you are going to be running many … Incentivized Helpful? Praveen Murugesan Engineering Manager - Ride Experience in Engineering at Uber (Internet, 5001-10,000 employees) Chose Apache Hive We selected Hive because it supports SQL, schema and provides structure on top of hadoop. Having data structured has its benefits, especially if there are thousands of users processing on the same data over and over again. Pig provides the ability to process unstructured data. … Incentivized Helpful? Verified User Chose Apache Hive Presto is slightly less reliable but much faster for interactive querying. These tools would not be replacements for each other, but rather complements. Incentivized Helpful? Verified User Chose Apache Hive Apache Hive was one of the first ways to query data out of a Hadoop cluster using SQL. However, there are many other tools out there that I believe will make Apache Hive a thing of the past. I have been working with in-memory data warehouses and other technologies that do not … Incentivized Helpful?
	Would buy again
	No answers on this topic	No answers on this topic
	Delivers good value for the price
	No answers on this topic	No answers on this topic
	Happy with the feature set
	No answers on this topic	No answers on this topic
	Lived up to sales and marketing promises
	No answers on this topic	No answers on this topic
	Implementation went as expected
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User Ratings
	Hadoop	Apache Hive
Likelihood to Recommend	8.0 (37 ratings)	8.0 (35 ratings)
Likelihood to Renew	9.6 (8 ratings)	10.0 (1 ratings)
Usability	8.0 (6 ratings)	8.5 (7 ratings)
Performance	8.0 (1 ratings)	- (0 ratings)
Support Rating	7.5 (3 ratings)	7.0 (6 ratings)
Online Training	6.1 (2 ratings)	- (0 ratings)
Data Sharing and Collaboration	7.7 (10 ratings)	- (0 ratings)
Data Sources	8.7 (10 ratings)	- (0 ratings)