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Apache Hive is a versatile software that has been widely used across various departments and organizations for different use cases. It has …
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What is Apache Hive?
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.
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What is Apache Hive?
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.
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Apache Hive Hadoop Ecosystem - Big Data Analytics Tutorial by Mahesh Huddar
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Connecting Microsoft Power BI to Apache Hive using Simba Hive ODBC driver
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Discover HDP 2.1: Interactive SQL Query in Hadoop with Apache Hive
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What is Apache Hive?
Apache Hive Technical Details
| Operating Systems | Unspecified |
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| Mobile Application | No |
Frequently Asked Questions
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.
Reviewers rate Usability highest, with a score of 8.5.
The most common users of Apache Hive are from Mid-sized Companies (51-1,000 employees).
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TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
Apache Hive is a versatile software that has been widely used across various departments and organizations for different use cases. It has proven to be particularly helpful in handling large datasets, migrating data between different operating systems, synchronizing programs, and fetching and generating product metrics. Users have found value in using Hive for data analytics, engineering, data science, product management, and IT-related tasks such as improving analysis of big datasets stored in Hadoop HDFS.
Furthermore, Apache Hive has simplified the process of filtering and cleaning data using SQL, reducing the learning curve for handling big data. It allows users to run SQL queries against data in Hadoop, enabling efficient analysis of large datasets without the need to learn a new language. Additionally, Hive has been utilized for building reports, analyzing data stored in the Hadoop file system, processing events gathered in HDFS, and converting them into parquet files for fast querying.
Overall, users have praised Apache Hive for its scalability, accessibility, and cost-effectiveness in storing and retrieving analytics data. It has provided an intuitive solution for storing large datasets, querying big sets of data using SQL, aggregating massive datasets into distilled information for data-driven decision making, and creating external and internal tables in Hadoop/BigData projects. With its ability to process both unstructured and structured data efficiently, Hive has become an essential tool for data analysts, engineers, and business analysts across organizations.
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Reviews
(1-8 of 8)Companies can't remove reviews or game the system. Here's why
April 12, 2022
Help your dev team !
We build our data lake and perform queries on large amounts of data. We group data from multiple sources into a common structure, making it easy for our developers to perform complex queries without leaving the simple framework provided by SQL. Although the deployment is not easy, once we have the infrastructure, the work is greatly simplified.
- Simplify query to devs
- Organize data
- Batch process
- Deploy
- Maintenance
- Support
April 08, 2022
It is an advance to the ease of the processes
The software is intuitive from the first steps, one of the first features we take into account for the software does not allow duplicate files to be stored. It is advanced software that through data the system constantly learns and develops. The first phase is very effective, the analysis and checking of the information are verified in detail.
- The unification of the data will help to establish the commercial criteria.
- We are sure that the data is protected
- If you try to extract an excessive amount of data, the system will become slow
- You may have the danger that the system collapses due to the amount of data
April 07, 2022
Excellent bigdata warehouse solution
Apache Hive is an open-source data warehouse solution built on top of Hadoop that helps to analyze a very large amount of data.
Our use case/scope is to work on a large data analytics project where the data frequency and velocity are very high. Apache Hive is very useful in processing both the unstructured and structured data in a seamless way. It help us in reducing to write complex queries as it is targeted to the SQL queries, we have a engineer team who are very proficient in writing SQL queries with the help of Apache Hive to process the big data.
We have identified no business issues using the solution.
Our use case/scope is to work on a large data analytics project where the data frequency and velocity are very high. Apache Hive is very useful in processing both the unstructured and structured data in a seamless way. It help us in reducing to write complex queries as it is targeted to the SQL queries, we have a engineer team who are very proficient in writing SQL queries with the help of Apache Hive to process the big data.
We have identified no business issues using the solution.
- Apache Hive supports external data tables.
- Supports data partitioning to improve overall performance.
- Apache hive is reliable and scalable solution.
- Apache Hive supports writing ad-hoc queries as well.
- Apache hive is not best suited for OLTP based jobs.
- Sometimes we observed high latency rate while querying data.
- Limitations on providing row-level data update.
- Training materials needs improvements.
September 21, 2020
Apache Hive: Big data querying tool w/SQL interface, but slower, more costly computation
We use Apache Hive to make data-driven decisions. It is used from finance to engineering to sales. It helps aggregate our massive data sets into distilled information.
- Flexibility through schema on read
- Familiar SQL like query language
- Functions for complex queries and analysis
- Slower processing than other tools on the market
September 19, 2020
Manage data for your warehouse as strong as a beehive using Apache HIve!
As we all know that, Apache Hive sits on the top of Apache Hadoop and is basically used for data-related tasks - majorly at the higher abstraction level. I work as an Assitant Professor at NIE, Mysuru and I am a user of Apache Hive since the first time I taught Big Data Analytics as a PG Course to my students.
It was one of those technical sessions and I was supposed to demonstrate a word count program of a novel downloaded from the Project Gutenberg. I was successfully able to download the novel, load it into the Hadoop platform and execute a HiveQL (a SQL similar syntax used by Apache Hive) query to demonstrate for few unique words, their count, and related examples.
It was one of those technical sessions and I was supposed to demonstrate a word count program of a novel downloaded from the Project Gutenberg. I was successfully able to download the novel, load it into the Hadoop platform and execute a HiveQL (a SQL similar syntax used by Apache Hive) query to demonstrate for few unique words, their count, and related examples.
- The capability to handle large amounts of data and its querying process.
- A syntax similar to SQL is an added advantage.
- An active developer support and community always ready to help.
- Ease of usage.
- Resource consuming sometimes. May be that I was using a larger object file.
- Needs to add an update or a modify functionality. This has to be the minimilastic CRUD requirement.
September 18, 2020
Apache Hive: SQL, open-source querying tool
Our company primarily uses Apache Hive to manage our data warehouse by being able to query multiple databases. We partition our tables as well as monitor query performance on very custom data queries by using this hive. Hive is only used by our data analysts and an overseas data warehouse team with only a few shared licenses existing on our virtual machines.
- Monitor query performance
- Manage tables in the data warehouse
- Uses standard SQL
- UI is quite dated and not intuitive
- Open-source, so does not have consistent updates or support
- Not the most optimal for ETL processes
September 13, 2017
Apache Hive Review
Hive is currently being used across the entire analytics organization at SurveyMonkey. The business problem that we solve through it is, accessing/storing large data sets(typically logs), in a scalable and accessible place.
- SQL like query engine, allows easy ramp up from a standard RDBMS
- Scalability is great
- If properly configured the data retreival is fantastic
- The way we currently have it implemented is quite slow, but I believe that's more of our implementation
- Joins tend to be slow
December 22, 2014
Hive, a very powerful open source data warehouse solution.
Score 10 out of 10
Vetted Review
Verified User
Hive is used by data team to store the largest datasets of the company. Data is partitioned in Hive and can be queried by Impala.
- Partition to increase query efficiency.
- Serde to support different data storage format.
- Integrate well with Impala and data can be queried by Impala.
- Support of parquet compression format
- Speed is slower compared to Impala since it uses map reduce