Apache Hive

Apache Hive

97 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Apache Hive	Score 8.2 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

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Apache Hive

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

Entry-level Setup Fee

No setup fee

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Community Pulse
	Apache Hive
Considered Both Products	Apache Hive Verified User Engineer 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 … Helpful? Prasanna Kumar TR Developer and Site Contributor Chose Apache Hive Apache hive gave more flexible than MS SQL server. Elasticsearch was little complex. GoogleBigQuery cost more. Incentivized Helpful? Verified User C-Level Executive 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 Engineer 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. 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 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 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 C-Level Executive 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 Administrator 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 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 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 Engineer 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 Strategist 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 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 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 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 Engineer 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 Analyst Chose Apache Hive [We selected Apache Hive because] It's from apache and opensource. So it's free. Incentivized Helpful? Jordan Moore Staff Consultant Chose Apache Hive Hive was one of the first SQL on Hadoop technologies, and it comes bundled with the main Hadoop distributions of HDP and CDH. Since its release, it has gained good improvements, but selecting the right SQL on Hadoop technology requires a good understanding of the strengths and … Incentivized Helpful? Tejaswar Rao Associate Consultant 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 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 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 Analyst Chose Apache Hive Hive is SQL compliant which makes it easy for the data folks compared to Pig Incentivized Helpful?
Top Pros	Pro Query data Pro Query language Pro Data analysis
Top Cons	Minus Not supported Minus Open source Minus Real time

Best Alternatives
	Apache Hive
Small Businesses	Google BigQuery Score 8.6 out of 10
Medium-sized Companies	Cloudera Enterprise Data Hub Score 9.0 out of 10
Enterprises	Oracle Exadata Score 8.2 out of 10
All Alternatives	View all alternatives

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)

User Testimonials
	Apache Hive
Likelihood to Recommend	Apache Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated. Incentivized Camilo Palacios Administrador informático. Read full review
Pros	Apache Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax. Relatively easy to set up and start using. Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved. Incentivized Verified User Anonymous Read full review
Cons	Apache Some queries, particularly complex joins, are still quite slow and can take hours Previous jobs and queries are not stored sometimes Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond). Sometimes, directories and tables don't load properly which causes confusion Incentivized Verified User Anonymous Read full review
Likelihood to Renew	Apache Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive. Yinghua Hu Senior Data Scientist Read full review
Usability	Apache Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain. Incentivized Verified User Anonymous Read full review
Support Rating	Apache Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup. Incentivized Ananth Gouri Assistant Professor Read full review
Alternatives Considered	Apache 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 Manjeet Singh Senior Manager - Engineering Read full review
Return on Investment	Apache Apache hive is secured and scalable solution that helps in increasing the overall organization productivity. Apache hive can handle and process large amount of data in a sufficient time manner. It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs. Incentivized Verified User Anonymous Read full review
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