Apache Hive

Apache Hive

95 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
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

Apache Hive

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

No setup fee

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Community Pulse
Key User Insights
	Apache Hive
Considered Both Products	Apache 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? Prasanna Kumar TR Developer and Site Contributor in Research & Development at ForgetCode.com (Computer Software, 1-10 employees) Chose Apache Hive Apache hive gave more flexible than MS SQL server. Elasticsearch was little complex. GoogleBigQuery cost more. Incentivized Helpful? Verified User Chose Apache Hive Community support and ease of use -not deployment. It enables querying and analyzing large amounts of data stored in HDFS, on the petabyte scale. It has a query language called HQL that transforms SQL queries into MapReduce jobs that run on Hadoop, and it is wonderful for the … Incentivized Helpful? Verified User Chose Apache Hive Apache Spark is similar in the sense that it too can be used to query and process large amounts of data through its Dataframe interface. Hive is better for short-term querying while Spark is better for persistent and long-term analysis. Another product is Impala. For our … Incentivized Helpful? Camilo Palacios Administrador informático. in Marketing at Logitech (Marketing & Advertising, 51-200 employees) Chose Apache Hive We have used a simple but necessary function such as merging certain data tables, which although they may be from different areas, complement each other or are necessary, you can use metadata if what you need is to validate the origin of your information and what impact it has, … Incentivized Helpful? 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? Pablo Gonzalez Internet Marketing Manager in Marketing at MKTi México (Marketing & Advertising, 51-200 employees) Chose Apache Hive We have used the system to migrate data either for new versions or because we will use another operating program, the software helps us to synchronize programs between different operating systems, a history of information can be kept constant, it can be sent to third parties … Incentivized Helpful? Verified User Chose Apache Hive Queries are easy to write and interface is similar to SQL so learning overhead is reduced. Multi user and data type support is provided. Can be easily scaled for very large amount of analytics. It is very flexible in terms of using file formats. Incentivized Helpful? Verified User Chose Apache Hive Due to effective queries resolved time and the performance and user-friendly framework compared to other products. 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? Manjeet Singh Senior Manager - Engineering in Engineering at Hike Messenger (Internet, 51-200 employees) Chose Apache Hive Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed 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? Verified User Chose Apache Hive Apache Hive decouples the query layer from the storage layer, it is more flexible and expandable. Incentivized Helpful? Ananth Gouri Assistant Professor in Engineering at The National Institute of Engineering, Mysuru (Education Management, 501-1000 employees) Chose Apache Hive One of the major advantages of using Presto or the main reason why people use Presto (Teradata) is due to that fact it can support multiple data sources - which is lacking as in the case of Apache Hive. But still, most people who come from a Structured data-based background … 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? Kartik Chavan Data Science Trainee in Information Technology at DivIHN Integration Inc (Electrical/Electronic Manufacturing, 1001-5000 employees) Chose Apache Hive I considered Hive because it is the best suited option when it comes to larger data access. Besides, learning HiveQL is comparatively easy. Incentivized Helpful? Verified User Chose Apache Hive I have used Storm for real-time processing, but that only addresses a few data points. But for a larger access to data, Hive is well suited. 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? Sameer Gupta Senior Data Analyst in Marketing at SurveyMonkey (Internet, 501-1000 employees) Chose Apache Hive I wasn't part of the evaluation process for Apache Hive. This was already implemented when I joined the company. I have worked with other big data plaftforms and I personally thinks most of them are quite comporable to one another. It really depends on what the company is going … 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?
	Would buy again
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	Delivers good value for the price
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	Happy with the feature set
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	Lived up to sales and marketing promises
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	Implementation went as expected
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User Ratings
	Apache Hive
Likelihood to Recommend	8.0 (35 ratings)
Likelihood to Renew	10.0 (1 ratings)
Usability	8.5 (7 ratings)
Support Rating	7.0 (6 ratings)