# Hive Reviews **Vendor:** The Apache Software Foundation **Category:** [Data Warehouse Solutions](https://www.g2.com/categories/data-warehouse) **Average Rating:** 4.2/5.0 **Total Reviews:** 60 ## About Hive Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. At the same time this language also allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL. ## Hive Reviews ### 1. User friendly and great tool for executing projects **Rating:** 5.0/5.0 stars **Reviewed by:** Nishmitha G. | Account Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** April 16, 2024 **What do you like best about Hive?** I like that it offers a highly customizable interface, enabling teams to organize task and manage workflow effectively. Easy to download and sort for reporting. **What do you dislike about Hive?** Easy to load information and access. I have no dislike. **What problems is Hive solving and how is that benefiting you?** Helps me in tabulating data and getting accurate figures. It allows me to streamline my workflows and improve collaboration with my team and perform anylysis more efficiently. ### 2. Robust app intended to reflect how you work day to day **Rating:** 4.5/5.0 stars **Reviewed by:** Ruth P. | Senior Allocator , Apparel & Fashion, Mid-Market (51-1000 emp.) **Reviewed Date:** July 25, 2023 **What do you like best about Hive?** Its exhilarating how well it seamlessly connects work, through its group messaging that spurs collaboration, its flexible project layouts, customer insights and reviews that help in strategy. **What do you dislike about Hive?** One thing to note is that its heavy on consumption and it requires enough ram to slow some integrated apps down. That's an issue that needs solving. **What problems is Hive solving and how is that benefiting you?** Its been using data analysis of the workflows to expose how work is actually being done, what's needed to optimize operations, how to schedule, allocate and much more. Its been a great help at getting everyone performing and moving as per timelines and objectives. ### 3. Hive Datawarehouse **Rating:** 5.0/5.0 stars **Reviewed by:** Poojitha S. | Team Lead, Enterprise (> 1000 emp.) **Reviewed Date:** July 24, 2023 **What do you like best about Hive?** Hive is the best Datawarehouse and open source. Easy to use. It has a query language HiveQL. The syntax is same as SQL. So it is easy to write the hive queries and easy to get reports and business insights. Best Olfor analytics. And easily integrated with Spark, Hadoop and cloud also. **What do you dislike about Hive?** Higher latency is the drawback. Developments should be made to improve the latency of the complex queries. **What problems is Hive solving and how is that benefiting you?** Helping us to get business insights and reporting. Helping us to analyse the data and draw some conclusions to improve the business. ### 4. The SUPERB PROJECT MANAGEMENT THAT HELPS ME stay organized **Rating:** 5.0/5.0 stars **Reviewed by:** Scott M. | Strategic marketing advisor, Food & Beverages, Mid-Market (51-1000 emp.) **Reviewed Date:** July 28, 2023 **What do you like best about Hive?** Fantastic and attractive UI Straightforward when it comes to tracking,assigning and monitoring projects Hive helps me keep track of all our projects and people connected to these projects **What do you dislike about Hive?** I don't have anything yet to state as a dislike I am satisfied in using hive **What problems is Hive solving and how is that benefiting you?** Managing the projects and getting the time logs ### 5. Data warehouse **Rating:** 3.5/5.0 stars **Reviewed by:** Nishu G. | Test Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** July 28, 2023 **What do you like best about Hive?** Open source framework allows to read and write and manage tha data like sql , HQl which makes it easy to use. **What do you dislike about Hive?** The latency in Apache hive is very high. **What problems is Hive solving and how is that benefiting you?** It provides SQL like query language called HQl with schema on read and transparently convert queries to map reduce. ### 6. Have reviews is a fantastic platform **Rating:** 4.5/5.0 stars **Reviewed by:** Anna F. | Associate marketing manager , Farming, Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2023 **What do you like best about Hive?** Hive offer tool's for project planning, including the ability for track project and timeline, create and assign tasks and manage resources. **What do you dislike about Hive?** I have no dislike towards hive since is the one I'm using **What problems is Hive solving and how is that benefiting you?** It allows users to analyse large amount structure and semi structure data ### 7. About Apache Hive **Rating:** 3.5/5.0 stars **Reviewed by:** Balaji A. | Data Engineering Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** February 16, 2023 **What do you like best about Hive?** I like the most in Apache Hive supports partitioning and bucketing for fast data retrieval. We can create custom UDF as per the requirements to perform data cleansing and filtering. It supports HQL similar to SQL which gives easy for the people who comes from SQL background. **What do you dislike about Hive?** Doesn't support OLTP and also doesn't support delete or update actions. **What problems is Hive solving and how is that benefiting you?** We have created a semantic layer in Hive that helps us to process the terabytes of data and generate the reports faster. it also helped us fault tolerance and high availability of the data ### 8. Hive review **Rating:** 3.5/5.0 stars **Reviewed by:** Aditya K. | Lead Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 17, 2022 **What do you like best about Hive?** It is easy to run query in hive as hive uses hql which is very similar to sql. Hive has hivemetastore service to save the metadata and hiveserver2 to serve the client requests so the segregation here helps in proper resource distribution. Hive is also fault tolerant which makes it ideal to run ETL long running batches **What do you dislike about Hive?** Hive has a problem of cold start and since it used mapreduce algorithm at the backend, it is way slower than spark which made us move to spark from hive as the job completion time after switching to spark got reduced by 70-80% **What problems is Hive solving and how is that benefiting you?** Informatica data ingestion Abinitio data ingestion and modifications Data formatting (as it provides option such as csv,parauet etc) Data transformation using hive query Data pipelines ### 9. Hive - For all the big data needs **Rating:** 4.5/5.0 stars **Reviewed by:** Yash K. | Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** August 22, 2022 **What do you like best about Hive?** Hive is a very valuable tool as it provides wrappers for data analysis and querying on Big data for organizations with huge amounts of data to be processed. It is built on top of Hadoop and makes SQL query building and storing quite convenient! **What do you dislike about Hive?** The biggest disadvantage of using Hive is that it does not provide or offer real-time queries and especially for row level updates as the latency is quite high in Hive. **What problems is Hive solving and how is that benefiting you?** Hive solves the problem of big data processing and analysis for me and my company. We are able to process and analyze huge amounts of data with the help of capabilities provided by Hive. It also allows parallel processing which makes it quite fast to use. ### 10. It works fine but needs improvements **Rating:** 3.5/5.0 stars **Reviewed by:** Cherukumalli S. | Administration, Small-Business (50 or fewer emp.) **Reviewed Date:** November 10, 2022 **What do you like best about Hive?** Flexible and easy to understand loved it **What do you dislike about Hive?** Not compatible with multiple platforms hence mostly plotform depend **What problems is Hive solving and how is that benefiting you?** Works best with ETL related works or tasks ### 11. Apache Hive review **Rating:** 4.5/5.0 stars **Reviewed by:** A P. | Freelance Data science/ big data trainer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 23, 2022 **What do you like best about Hive?** File formats for optimizations, external **What do you dislike about Hive?** cannot analyse unstructured data, not much faster when it comes to complex operations on very huge data **Recommendations to others considering Hive:** If you have big data and using Hadoop or cloud to store it. You can use Hive to analyze and generate reports. You can even integrate Hive with sqoop to analyze structured data from RDBMS as well as unstructured data in Hadoop like systems **What problems is Hive solving and how is that benefiting you?** adhoc analytics and batch analytics on big data ### 12. Good data distribution **Rating:** 4.5/5.0 stars **Reviewed by:** Akshay P. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 20, 2022 **What do you like best about Hive?** The data distribution and data processing in hive is very good in hive. DDL and DML functions in hive are better than conventional sql databases. Hive is better known for fault resistance. **What do you dislike about Hive?** The data output on hive is very slow. The data processing is very slow and the output is delayed due to this slow processing. Also the syntax is bit complex than conventional sql language. **Recommendations to others considering Hive:** The DML processing needs to get faster. **What problems is Hive solving and how is that benefiting you?** Fault tolerance is very good feature which helps in data storing. Incase one database is lost, there isna backup created and this database can retrieved easily and intact. ### 13. Best Data Wharehouse tool for huge volume of structured data **Rating:** 5.0/5.0 stars **Reviewed by:** Kubendra Reddy M. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** February 17, 2022 **What do you like best about Hive?** Best thing about Hive is it alows us to write the code in sql for processing and managing the data. It allows us to partition and distribut the data among the cluster machines. We can also choose execution engine like spark, tez,mapredice while rinning in hive. If you your processing and analysing the bulk volume of batch data then hive is best. **What do you dislike about Hive?** It supports only structure data and we can't do updates too. Only supports OLAP. **Recommendations to others considering Hive:** Definitely go for it. **What problems is Hive solving and how is that benefiting you?** We are managing our data warehouse for analytical purpose using hive. We used to partition and cluster the tables for better parallel processing and less shuffling so the processing will be optimised. We used to read the hive tables with spark too for better computation and speed. ### 14. Hive Review for big data **Rating:** 3.5/5.0 stars **Reviewed by:** kirankumar k. | Big Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 03, 2022 **What do you like best about Hive?** The friendliness of the data warehouse tool for the database developers **What do you dislike about Hive?** Not inclusion of acid properties, it doesn't have the acid properties as in the databases **What problems is Hive solving and how is that benefiting you?** I usually use hive for my big data [data migration problems], the speed at which the query operates, and the option to choose various engines ### 15. Great Experience. **Rating:** 2.5/5.0 stars **Reviewed by:** franco g. | Asistente jurídico, Small-Business (50 or fewer emp.) **Reviewed Date:** August 24, 2021 **What do you like best about Hive?** Hive is a data warehousing infrastructure built on top of Hadoop to provide data grouping, querying, and analysis. Apache Hive supports the analysis of large datasets stored under Hadoop's HDFS and in compatible systems like the Amazon file system. It offers a SQL-based query language called HiveQL5 with schemas to transparently read and convert queries in MapReduce, Apache Tez6, and Spark tasks. All three execution engines can run under YARN. To speed up queries, Hive provides indexes, which include bitmap indexes. **What do you dislike about Hive?** Offers many tools, has great growth potential **Recommendations to others considering Hive:** It is a software that allows you to enhance the performance of your company. **What problems is Hive solving and how is that benefiting you?** Possibility of storing metadata in an organized and easily accessible way. ### 16. good to deal with large and partitioned data **Rating:** 4.5/5.0 stars **Reviewed by:** Rakesh S. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** June 05, 2021 **What do you like best about Hive?** the ease of use and its interface is best **What do you dislike about Hive?** running of queries in slow mode of map-reduced **What problems is Hive solving and how is that benefiting you?** storing the large data and retirving it through queries ### 17. Best **Rating:** 5.0/5.0 stars **Reviewed by:** Rameez R. | Information Technology Team Lead, Enterprise (> 1000 emp.) **Reviewed Date:** April 27, 2021 **What do you like best about Hive?** Good querying on hive databases.and easy to create schemas **What do you dislike about Hive?** It does not allow datatypes conversion. As it will result in lost of data **What problems is Hive solving and how is that benefiting you?** Querying on hive dbs. Also hs2 and hive metastore resulting fast results ### 18. I am working on hive from last 2 years **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Food & Beverages | Small-Business (50 or fewer emp.) **Reviewed Date:** April 22, 2021 **What do you like best about Hive?** It's performance using distributed computation **What do you dislike about Hive?** Limited options for query performance optimization **What problems is Hive solving and how is that benefiting you?** It is very good for OLAP related tasks ### 19. A complete dataware house tool **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Banking | Enterprise (> 1000 emp.) **Reviewed Date:** April 21, 2021 **What do you like best about Hive?** Schema on any format HDFS files. Easy to download the data. A complete tool similar to database tool like toad. **What do you dislike about Hive?** Performance,sometime it is very difficult to run queries. Gui can be improved with more user friendly options **What problems is Hive solving and how is that benefiting you?** Data processing for regulatory reporting ...maintain lineage ### 20. Hive makes querying in HDFS much easier, but not optimized or fast enough **Rating:** 4.5/5.0 stars **Reviewed by:** Elisa L. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** July 23, 2019 **What do you like best about Hive?** Otherwise, if you write it as a normal SQL, it may take hours to process. But it is a bit different from standard SQL. Personally speaking, I use Hive mainly for ad hoc queries and reports. It is a data warehousing software that facilitates querying and managing large datasets residing in distributed storage. **What do you dislike about Hive?** Performance tuning is difficult and becomes challenging for complex queries, it still has some bugs, such as all data going to a single reducer, which can slow down query results. -> Some SQL operations do not work in Hive, such as non-equality joins, data cannot be updated, but we will have to rewrite. **Recommendations to others considering Hive:** Keep your big data in HDFS and configure Hive there. Use the latest versions of Hive, it is faster and better for big data analysis. **What problems is Hive solving and how is that benefiting you?** We are developing Hive For people who are used to writing SQL queries, it would be very good to use Hive on top of Hadoop for files stored in HDFS. Dumping Site Activity Big Data streaming data, as well as data logs in Hive We are developing Hive ### 21. slowest database ever, overcomplicates simple sql language, **Rating:** 1.5/5.0 stars **Reviewed by:** Daniela S. | Digital Project Manager, Internet, Enterprise (> 1000 emp.) **Reviewed Date:** October 21, 2019 **What do you like best about Hive?** nothing in particular. helps us with big data and allows all users to have unrestricted bandwidth, but we already ran into issues with that, so now one of the servers has limitations. **What do you dislike about Hive?** . at my company it was fairly troublesome getting access since it's underlying warehouseing is in hadoop, then have to connect through hive **What problems is Hive solving and how is that benefiting you?** data insights with big browser data through mapreduce ### 22. Great for complex data structures like arrays of strucs **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Leisure, Travel & Tourism | Enterprise (> 1000 emp.) **Reviewed Date:** August 25, 2019 **What do you like best about Hive?** I was a top fan of Impala for a while until I reached a series of limitations that were impossible to overcome. I work a lot with arrays and just the fact of being able to use array_contains in impala made me switch to Hive. Also, we are moving fast on the direction of self made Macross for hive that let us do complex queries without lateral view explodes **What do you dislike about Hive?** Session creation takes a while and speed is quite slow when comparing to Impala **Recommendations to others considering Hive:** Try to explore the reduce_array or self made macross **What problems is Hive solving and how is that benefiting you?** Complex data analysis with tables that have several billion rows by partition ### 23. Great map reduce SQL like engine **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Telecommunications | Enterprise (> 1000 emp.) **Reviewed Date:** May 06, 2019 **What do you like best about Hive?** It is highly flexible in configurations. So many options to load data from- directly from linux file system or hdfs. You can create external and managed tables. One fun feature is that you can shoot bash commands from hive as well **What do you dislike about Hive?** It cannot be used for streaming data. Error logging can be improved so that error tracking and resolution can be more efficient. **Recommendations to others considering Hive:** Great map-reduce framework for batch processing **What problems is Hive solving and how is that benefiting you?** It is used to transform and process Big Data datasets in batches. It can handle TBs of data. Push predicate feature has greatly improved the performance of the queries and the developer doesn't need to think about it anymore ### 24. SQL on Hadoop **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Retail | Enterprise (> 1000 emp.) **Reviewed Date:** March 23, 2019 **What do you like best about Hive?** - Easy to use interface - multiple clients (CLIs) - easy to debug issues with the help of fully descriptive logs - constantly the product is being improved to meet all the DB developer requirements - can be accessed from multiple applications - access through knox for additional security - no indexing - multiple file formats - the tez architecture **What do you dislike about Hive?** - authentication gaps - issues when routing through zookeeper - not as matured tool as the regular database tools **Recommendations to others considering Hive:** - Highly recommend **What problems is Hive solving and how is that benefiting you?** - BI team is helping all the enterprise users to ingest and access data from hadoop - most of the users are well versed with standard sql tools - to make hadoop enterprise wide solution we are training all users with hive ### 25. Easy intro to big data **Rating:** 4.5/5.0 stars **Reviewed by:** Kevin P. | Enterprise (> 1000 emp.) **Reviewed Date:** July 20, 2018 **What do you like best about Hive?** Ease to get started. Leverages sql knowledge. Has reasonable documentation. Fast to write queries. **What do you dislike about Hive?** Documentation sparse in some areas such as datetime formats. Queries run slowly and often fail to complete. **Recommendations to others considering Hive:** Hive is good for running quick ad hoc queries and performing simple preprocessing. **What problems is Hive solving and how is that benefiting you?** Preprocessing for machine learning pipeline. Running ad hoc queries on customer databases to generate high level summaries. ### 26. Hive is useful but can be quirky **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Internet | Mid-Market (51-1000 emp.) **Reviewed Date:** January 10, 2018 **What do you like best about Hive?** The best thing about HIVE is that anyone that is familiar with SQL can take advantage of HIVE's ability to run map reduce jobs. Newer version of HIVE is getting better at supporting windowing functions and fleshing out any inconsistencies. So far the documentation is good enough for getting me through my tasks and there is still on-going support for this product, which is a pretty good sign to me. **What do you dislike about Hive?** Older versions of HIVE sucks. There are lots of limitations that will force you to write HiveQL queries that are not straight forward and, even potentially, inefficient. For example, no support for window functions and no equality comparisons on joins can make your life very difficult so you will need to fall back to using some whacky full joins or self joins to accomplish the same task. **What problems is Hive solving and how is that benefiting you?** We are using HIVE as a data warehouse. One of the benefits of HIVE is that it can break your SQL queries into a series of map reduce jobs, so its supposed to speed up your queries if given enough compute nodes. ### 27. HIve Review - Data Science Perspective **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Mid-Market (51-1000 emp.) **Reviewed Date:** January 04, 2018 **What do you like best about Hive?** Hive is the best out there for answering ad-hoc queries in parallel paradigm. It works very well with Hadoop Echo system (mainly integrates perfectly with HDFS). - Easy to use as it implements most of SQL functions. **What do you dislike about Hive?** - Needs more optimization for complex queries (like caching, auto-partitioning,etc ...) to speed up the latency of the queries. - Tuning the hive parameters is really challenging for the users. The default settings don't work with the large queries. - Hive is perfect if 90-95% of the queries are read-only. It is not suitable for applications with heavily updates **What problems is Hive solving and how is that benefiting you?** Get quick insights from big data in case of the customers' data don't fit on one machine. It helps a lot for data preparation (i.e. creating temporary tables), that can be consumed by other machine learning solutions like Spark to build machine learning models that add more business values. ### 28. Hive review for its use in big data applications **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** October 10, 2017 **What do you like best about Hive?** Hive is great for handling logs in big data projects. We are using the same in our project and it is great for using joins and grouping which is very difficult and tricky in map reduce. It has a lot of udf packages and it is very easy to add new udfs. We were also using bucketing and clustering to optimize the query. Concept of external tables and the way we can manipulate data even when table is deleted from hive is really amazing. Lot of connectors available in the market for different softwares. **What do you dislike about Hive?** The thing which I dislike is latency and the way it saves data. While inserting data I have to wait a lot of few records. Compiler execution plan is very immature as it does not do proper query optimization. Though the community is working fast for overcoming quickly but I think it will take time for hive to be **Recommendations to others considering Hive:** Yes, I would highly recommend this product as this helps to solve a lot of problems mainly for logs. It has lots of connectors and so compatibility issues are not there. You can use it with hbase , tableau etc. So, its worth using. **What problems is Hive solving and how is that benefiting you?** We are using hive mainly for saving our logs. it helps us to keep track of what records are inserted, which records have failed and what are relationship between them. we are using tableau for analyzing data . ### 29. the hive - best in class tool **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Defense & Space | Enterprise (> 1000 emp.) **Reviewed Date:** December 03, 2017 **What do you like best about Hive?** If you are data analyst and expert in SQL then use Hive. Hive is very easy to work with especially if you are a SQL person. I use both hive and pig at work. I use hive mainly for ad hoc quires and reports. For BI reports Hive is the best since you can reuse all the SQL that you have done for traditional data warehouses. Also with Hive Server2 you get a real JDBC support so you can plug your BI tools to it. Many more SQL features like cubes, rollups, windowing, lag, lead, etc are being added to Hive through Hortonworks Stinger initiative. Hive also produces very compact code, which is always good for reading and debugging. **What do you dislike about Hive?** I would suggest to use hive for large projects, where you want to implement SQL-like data access, schemas, metadata, partitions, server-based deployment, jdbc, etc. Pig is a good language and can be very handy for immediate tasks or small projects. i would recommend PIG for small projects . **Recommendations to others considering Hive:** Hive Hadoop provides the users with strong and powerful statistics functions. Hive Hadoop is like SQL, so for any SQL developer the learning curve for Hive will almost be negligible. **What problems is Hive solving and how is that benefiting you?** Hive Hadoop provides the users with strong and powerful statistics functions. Hive Hadoop is like SQL, so for any SQL developer the learning curve for Hive will almost be negligible. Hive Hadoop can be integrated with HBase for querying the data in HBase whereas this is not possible with Pig. In case of Pig, a function named HbaseStorage () will be used for loading the data from HBase. Hive Hadoop has gained popularity as it is supported by Hue. Hive Hadoop has various user groups such as CNET, Facebook, and Digg and so on. ### 30. Hive gives you flexibility to query data in hadoop **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Insurance | Enterprise (> 1000 emp.) **Reviewed Date:** July 31, 2018 **What do you like best about Hive?** Leverage sql skills to perform operations on data stored in hadoop. **What do you dislike about Hive?** Works on map reduce algorithm, so the retrieval of data is a little slow. **What problems is Hive solving and how is that benefiting you?** Allowed business users to query data using sql skills. ### 31. TheHive **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Networking | Enterprise (> 1000 emp.) **Reviewed Date:** November 27, 2017 **What do you like best about Hive?** For all its processing power, Pig requires programmers to learn something on top of SQL. It requires learning and mastering something new. Hive statements are remarkably similar to SQL and despite the limitations of Hive Query Language (HQL) in terms of the commands that it understands, it is still very useful. Hive provides an excellent open source implementation of MapReduce. It works well when it comes to processing data stored in a distributed manner, unlike SQL which requires strict adherence to schemas while storing data. **What do you dislike about Hive?** Despite the working differences, once you enter the Hive world from SQL, similarity in language ensures smooth transition but it is important to note the differences in constructs and syntax, else you’re in for frustrating times. **What problems is Hive solving and how is that benefiting you?** data extracting, processing and analysis. It's fast. ### 32. Big Data with SQL **Rating:** 4.0/5.0 stars **Reviewed by:** Dhharvi S. | System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 27, 2017 **What do you like best about Hive?** Hive provides an ease to the user who wants to store bulk data, in a tabular manner. It works on the same queries like SQL, making it easy for using the traditional database system. Because of this reason, people need not have to study some new language and can still adapt to the Big Data Culture. Also it has features like partition, and bucketing, helping in segregation of data. Data can directly be loaded into hive, by HDFS, using the CSV files of the same format, or from Hbase by making a pointer to the Hbase table, providing a link within Hadoop. **What do you dislike about Hive?** For small amount of data also, it runs map reduce job, which consumes some time, and thus is not efficient for the same. We do not have a concept of primary key in Hive, so we can have redundant entries. Also till the older version, update and delete were not possible, and now also in the new version, if we want to use the update and delete commands, the performance of the tool gets degraded. **Recommendations to others considering 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. **What problems is Hive solving and how is that benefiting you?** We are using Hive for storing logs, of data, being generated, in our business. Further we will be using these logs for reconciliation purpose, helping in keeping a track of data. ### 33. Excellent Batch Query Tool **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Internet | Mid-Market (51-1000 emp.) **Reviewed Date:** November 28, 2016 **What do you like best about Hive?** Stable product; Easy to use; Multiple computation engines - Tez, MR; Almost all SQL capabilities; **What do you dislike about Hive?** Delete support is still not there even though they are nearly there. **Recommendations to others considering Hive:** Hive is production ready for all batch queries. But it has more flags than UN building :) **What problems is Hive solving and how is that benefiting you?** Primary Querying engine for Data Analytics ### 34. Fast Queries for BI use cases **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Internet | Mid-Market (51-1000 emp.) **Reviewed Date:** October 25, 2016 **What do you like best about Hive?** Provides quick results based on a hadoop database, easy to use interface with simple set up steps **What do you dislike about Hive?** Some quirks with HiveQL may require referencing the documentation, but there is a lot of similarity with other SQL based languages. **What problems is Hive solving and how is that benefiting you?** Data analytics, making vast amounts of data available for general BI uses ### 35. Hive as the base for BI tools to get data from Hadoop **Rating:** 4.0/5.0 stars **Reviewed by:** Pavlo S. | Senior Software Engeneer, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** July 15, 2015 **What do you like best about Hive?** The Hive is intended to simplify your experience with Hadoop and allows developers and business analyst apply their SQL knowledge to query data, build reports, build etl etc. **What do you dislike about Hive?** As the open source software it has common issues with support. Also Hive doesn't support many features that traditional SQL has. **Recommendations to others considering Hive:** The Hive and Hadoop is not a database in classical understanding, and the purpouse is to proceed the big volumes of data. But in case you'll try to query some small table you'll notice that it can take x1000 more time to get resulting the data. Hive doesn't work with single record and it should not be considered as persisnent arrea for biling like systems. **What problems is Hive solving and how is that benefiting you?** The main purpouse of using Hive is to building reports and do analysis of data that is stored in the Hadoop file system. As for now it is the only one framework that can be used by all most popular BI tools to read the data from the HDFS. ### 36. Hive is a great tool to have in a hadoop ecosystem, works great in generating parquet files **Rating:** 4.0/5.0 stars **Reviewed by:** Sanjeev C. | Director of Engineering, Analytics, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** July 08, 2015 **What do you like best about Hive?** To be able to run map reduce jobs using json parsing and generate dynamic partitions in parquet file format. **What do you dislike about Hive?** It is slow compared to Spark/Impala for most operations. Also, it throws Out of Memory if multiple partitions are updated containing many parquet files. **Recommendations to others considering Hive:** Explore other tools like Spark also as many of the features that Hive does is now supported by Spark. **What problems is Hive solving and how is that benefiting you?** Events are gathered in HDFS by flume and needs to be processed into parquet files for fast querying. The input data contains variable attributes in the json payload as each customer could define custom attributes. It is part of the ETL pipeline, where hive jobs read json data and generates parquet files that would be queried using impala/spark. Using views, each customer queries only the relevant data. ### 37. One among many to do ETL **Rating:** 2.5/5.0 stars **Reviewed by:** Bharadwaj (Brad) C. | Director Of Engineering/Head of Reliability Engineering, Enterprise (> 1000 emp.) **Reviewed Date:** July 17, 2015 **What do you like best about Hive?** Hive syntax is almost like sql, so for someone already familiar with sql it takes almost no effort to pick up hive. But there are other tools that can do the same thing faster these days. Hive initially was really good to have; but more and more projects are now available to do SQL like operations on Big Data (like Drill). **What do you dislike about Hive?** Hive is comparatively slower than its competitors. Its easy to use but that comes with the cost of processing, If you are using it just for batch processing then hive is well and fine. It also does not have as rich of a scripting language. **Recommendations to others considering Hive:** Have better tools if you invest some more time/effort **What problems is Hive solving and how is that benefiting you?** In Retail, the business partners are more comfortable querying their own data instead of relying on Engineers. Hive solves one of that problems. The main purpouse of using Hive is to building reports and do analysis of data that is stored in the Hadoop file system. ### 38. For all the batch operations! **Rating:** 4.5/5.0 stars **Reviewed by:** Pradeepkumar K. | Big Data Engineer, Internet, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2015 **What do you like best about Hive?** The syntax of hive! Its almost SQL so its easy to use. External tables, partitions, buckets, UDFs all the features I like to use with hive. ORC data format occupying lesser space and retrieving the data much faster. Learning curve looks easier as it is similar to SQL but hold on! you must learn all the features of hive before writing a big hql to join multiple hundreds GBs tables and fetch results. Otherwise if you write it like a regular SQL it may take hours to process. So hive is always at its best when you set the optimization parameters before you run your scripts. Also its complex datatypes make hive more useful than other RDBMS. **What do you dislike about Hive?** Hive is comparatively slower than its competitors. Its easy to use but that comes with the cost of processing, If you are using it just for batch processing then hive is well and fine. **Recommendations to others considering Hive:** If you are looking for some easy to use big data product to run queries and generate reports on batch mode then Hive is the tool! **What problems is Hive solving and how is that benefiting you?** Generating datasets from huge files for reporting purposes. ### 39. Great tool for quick analyses **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Internet | Enterprise (> 1000 emp.) **Reviewed Date:** July 08, 2015 **What do you like best about Hive?** Hive syntax is almost exactly like sql, so for someone already familiar with sql it takes almost no effort to pick up hive. It can perform a wide variety of analyses over very large sets of data and requires very little tuning if you are willing to wait a while for the results. **What do you dislike about Hive?** Hive can be a bit slow in comparison to other languages like Pig. It also does not have as rich of a scripting language. This is what makes it the second choice language for most data analysis jobs at LinkedIn. **Recommendations to others considering Hive:** I'd take a look at the user forums to see all the newest additions to Hive and I'd also consider whether your main use-case is scripting vs on-off analyses. I primarily use hive (so do many devs) to do our analyses since hive is trivially simple to use and it does pretty much everything sql will do, but it's not great for scripts and loading data into files, so if that is your use-case I'd consider looking into other options. **What problems is Hive solving and how is that benefiting you?** We are trying to mine data from massive data sets for a wide variety of purposes (debugging production issues, creating business metrics, models, and forecasts among other things). We have been able to do this very easily using our data warehouse and a combo of hive and Pig. ### 40. Great distributed storage for hadoop **Rating:** 4.0/5.0 stars **Reviewed by:** Anubhav A. | Big Data Engineer, Marketing and Advertising, Small-Business (50 or fewer emp.) **Reviewed Date:** July 09, 2015 **What do you like best about Hive?** Ease of use as well as ability to scale. It has proven its reliability. They have continued to add more features and increased its speed at the same time. **What do you dislike about Hive?** Speed is still slower compared to newer distributed warehouses. Also, it still uses mapreduce behind the scene which is very slow in the present days. **Recommendations to others considering Hive:** Its great but do not use for real time application. **What problems is Hive solving and how is that benefiting you?** Storing large amount of data that could not fit in to any relational database system. Being able to derive valuable insight into our data by running mapreduce jobs on data stored in Hive. ### 41. Hive is easy to scale. **Rating:** 5.0/5.0 stars **Reviewed by:** Pengcheng X. | Member of Technical Staff, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** April 09, 2015 **What do you like best about Hive?** Hive is one of the Apache projects. it is a data warehouse software which facilitates querying and managing large datasets residing in distributed storage. It provides a way to enable easy data extract/transform/load (ETL) Some of the nice features include (1) a simple SQL-like query language, called HiveQL, that enables users familiar with SQL to query the data. But it is a bit different from SQL standard. For example, HiveQL can also be extended with custom scalar functions (UDF's), aggregations (UDAF's), and table functions (UDTF's). (2) You can define your own read or written data format called Hive SerDe. (3) Hive can be run on Hadoop and HDFS. It has very good scalability. Personally speaking, I use hive mainly for ad hoc quires and reports. For BI reports Hive is the best since you can reuse all the SQL that you have done for traditional data warehouses. Also with Hive Server2 you get a real JDBC support so you can plug your BI tools to it. Many more SQL features like cubes, rollups, windowing, lag, lead, etc are being added to Hive through Hortonworks Stinger initiative. Hive also produces very compact code, which is always good for reading and debugging. **What do you dislike about Hive?** Too large code base. It is hard to maintain and support. And, there are too many configurations. If you take a look at the HiveConf.java, you will be confused with so many configurations there. It is easy to get lost when you configure them. And, if you configure some of them in a wrong way, you may suffer from bad query performance. **Recommendations to others considering Hive:** Strongly recommend. **What problems is Hive solving and how is that benefiting you?** We are developing Hive. Hive is part of our product ### 42. Use it most of the time working with big data **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Consumer Services | Mid-Market (51-1000 emp.) **Reviewed Date:** April 22, 2015 **What do you like best about Hive?** It is very simple to use because you fill like you use simple SQL language for querying data. When I just started I didn't have any experience with Hive and in like one week I was able to query big data and do some analysis. In a month I was able to administrate data and create my own databases with the useful data. . . **What do you dislike about Hive?** Not so many implemented functions in the Hive. There are very useful Window functions but it's not enough. . . It's not that simple to modify data inside a table. . . **Recommendations to others considering Hive:** Keep your big data on hdfs and setup Hive there. It's very easy to use and very helpful especially for new users or someone who just started with big data. . . . . . . . . . . . . . . **What problems is Hive solving and how is that benefiting you?** Analyze every day and every hour or even every minute user experience, user behavior in application or web client , etc . . . ### 43. Works great for batch-processing large datasets **Rating:** 3.5/5.0 stars **Reviewed by:** Abhishek G. | Senior Software Engineer, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** April 02, 2015 **What do you like best about Hive?** - Easy to learn - Can query complex data including nested structures. - Flexible (wrt data schema) - With ORC SerDe, I/O can be reduced drastically - by reading only what is required (columnar formats). **What do you dislike about Hive?** - Needs schema to be defined in prior. - Not ANSI SQL compliant. - Not suitable for fast interactive queries, even on moderate size datasets. - Works only with Hadoop (not an independent query-processing tool) - Not enterprise grade w.r.t quality of documentation, error messages, support **Recommendations to others considering Hive:** I only explored this for a personal project in school. Hence this is only a personal view. It's surely good to try out and see for yourself. **What problems is Hive solving and how is that benefiting you?** Exploring ways to store and process semantic datasets ### 44. I am a Premier Support Engineer for Hortonworks. I install, support, and use Hive heavily. **Rating:** 5.0/5.0 stars **Reviewed by:** Prabir G. | Hadoop Engineer, Defense & Space, Mid-Market (51-1000 emp.) **Reviewed Date:** July 09, 2015 **What do you like best about Hive?** 1) ability to handle PetaByte scale of data 2) ability to work with near SQL query language 3) schema on read capibility **What do you dislike about Hive?** 1) optimizer technology is still maturing **Recommendations to others considering Hive:** For the right use cases, there is practically no alternative **What problems is Hive solving and how is that benefiting you?** 1) handling huge datasets 2) handling semi-structured and structured data sets with the same tool ### 45. Its good for Business Analysts and its good for pulling the data for analysis from Hadoop **Rating:** 3.5/5.0 stars **Reviewed by:** Anusha B. | Teaching Assistant for Big Data Systems, Higher Education, Enterprise (> 1000 emp.) **Reviewed Date:** April 20, 2015 **What do you like best about Hive?** If you know how to write sql statements you can write hiveql and it doesn't require you to learn anything new,its pretty straightforward **What do you dislike about Hive?** Performance tuning is difficult and becomes hard for complex queries, it still has a few bugs like all the data going to single reducer, which might lead to slow down the query results. **Recommendations to others considering Hive:** Use latest versions of hive, its faster and better for big data analysis **What problems is Hive solving and how is that benefiting you?** For developing reports for business analysts, lot of them know sql statements so its easy to write and pull information for analysis ### 46. Why I don't like Hive as much (as Pig) **Rating:** 1.5/5.0 stars **Reviewed by:** Siyu Y. | Staff Software Engineer, Internet, Enterprise (> 1000 emp.) **Reviewed Date:** July 13, 2015 **What do you like best about Hive?** Easy SQL like syntax for very short and simple queries **What do you dislike about Hive?** No alias for relation. No flow controls as well. **What problems is Hive solving and how is that benefiting you?** I build machine learning model for online advertising system. Hive to me is more like a ad-hoc query engine rather than a platform where I can develop complex algorithm on ### 47. Active Hive user since last 2 years **Rating:** 4.0/5.0 stars **Reviewed by:** Ankit M. | Software Developer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** July 08, 2015 **What do you like best about Hive?** The best part about hive is that it easy to master because of its SQL like interfacing. Also very handy tool for ETL and DW functions. **What do you dislike about Hive?** Not too good with setting up optimization parameters. Need to remember a lot of console settings. Index doesnt turn out to be very useful. CRUD functions have many pre-requisites like the table must be bucketed, etc. **What problems is Hive solving and how is that benefiting you?** we are trying to create a standard ETL pipelining tool that would support standard BI/Reporting utilities. ### 48. It was wonderful! **Rating:** 4.5/5.0 stars **Reviewed by:** Daryl R. | Admissions Data Processor - School of Education and Counseling Psychology, Higher Education, Small-Business (50 or fewer emp.) **Reviewed Date:** July 13, 2015 **What do you like best about Hive?** Its very user friendly. Easy to install and use. I like the interface very much . **What do you dislike about Hive?** Nothing I can think of. I had a great experience working on HIVE and was satisfied with all the features as it met all my requirements. **What problems is Hive solving and how is that benefiting you?** I was working on a school project as a part of Big Data course and executing queries with HIVE made the whole project lot more simpler. ### 49. Used as a way for Data Scientists to easily query HDFS data **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** July 08, 2015 **What do you like best about Hive?** The ability to view HDFS data in a relational format and easily query it through HiveQL **What do you dislike about Hive?** The fact that it uses MapReduce whether you query a pre existing table or a perform a complex query. Tez helps with this issue. Also the inability to delete/update data is a real issue and forces other services to be used eg HBase. **Recommendations to others considering Hive:** Index index index! **What problems is Hive solving and how is that benefiting you?** The ability to use Hive on HUE is perfect. We are building a platform for data scientists (prefer GUI to shell) to perform analysis so removing the need for command line is excellent. ### 50. Hive - Scalable Query Language for Hadoop **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** July 08, 2015 **What do you like best about Hive?** performing SQL-like queries, Partitioning Tables, De-normalizing data, Compress map/reduce output are best benefits **What do you dislike about Hive?** For some cases you cannot do complicated operations using Hive e.g. when output of one job acts as input to the other job (SequenceFileFormat file) or writing query on an image file, Hive is not useful. **What problems is Hive solving and how is that benefiting you?** Hive helps in resolving big data problems ## Hive Discussions - [What is Hive workflow?](https://www.g2.com/discussions/what-is-hive-workflow) - [What is the Hive platform?](https://www.g2.com/discussions/what-is-the-hive-platform) - [How do I use Hive software?](https://www.g2.com/discussions/how-do-i-use-hive-software) - [What does hive software do?](https://www.g2.com/discussions/what-does-hive-software-do) - [How does this compare to other SQL-like languages?](https://www.g2.com/discussions/how-does-this-compare-to-other-sql-like-languages) - 1 upvote - [View Hive pricing details and edition comparison](https://www.g2.com/products/hive/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-13+12%3A13%3A30+-0500&secure%5Bsession_id%5D=21363db4-f2c8-472b-9f14-e904a1dfdaab&secure%5Btoken%5D=5cfd4e02577fc6165d19051bbd8b521039498301f20eabcc3e610dc0538e8d68&format=llm_user) ## Hive Features **Data Management** - Data Integration - Data Compression - Data Quality - Built-In Data Analytics - In-Database Machine Learning - Data Lake Analytics **Integration** - BI Tool Integration **Deployment** - On-Premise - Cloud **Performance ** - Scalability **Security** - Data Governance - Data Security **Generative AI** - AI Text Generation - AI Text Summarization ## Top Hive Alternatives - [Snowflake](https://www.g2.com/products/snowflake/reviews) - 4.6/5.0 (687 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,156 reviews) - [Teradata Vantage](https://www.g2.com/products/teradata-teradata-vantage/reviews) - 4.3/5.0 (345 reviews)