# Apache Hive Reviews 2026. Verified Reviews, Pros & Cons | Capterra > Is Apache Hive the right ETL solution for you? Explore 17 verified user reviews from people in industries like yours to make a confident choice. Source: https://www.capterra.com/p/170238/Apache-Hive/reviews --- Apache Hive 4.2 (17) Provider data verified by our Software Research team, and reviews moderated by our Reviews Verification team. [Learn more](https://www.capterra.com/our-story/) * * * Last updated March 13th, 2026 # Reviews of Apache Hive Ease of use 4.1 Customer Service 4.2 ## Showing most helpful reviews Showing 1-17 of 17 Reviews Sort by: Most Helpful Rating Company Size Reviewer's Role Length of Use Frequency of Use Monish K. senior software engineer Computer Software Used the software for: 2+ years ### "SQL approach of processing data from a distributed file system" April 20, 2020 4.0 I am having a Good Experience, Hive Has been a great help to the big data world, performance is the only problem which is reasonable since it has to deal with distributed file system Pros Data on a distributed filesystem such as HDFS or S3 can be used directly for processing and modified using SQL with the help of HIVE, No need for writing complex java programs for executing map reduce, HIVE as implemented a SQL way of executing Map Reduce job's Hive has many configuration queries which increases the scope of optimisation for the under ling MR jobs, example sort mb , parallelism, number of reducers, size per reducer etc ... Hive tables data are always stores on files, even if its not a external table, these files can be directly used as a input for a MR job HIVE sql syntaxes are quit similar to that of mysql, HIVE provides good java libraries, such as sqoop which helps data table schema and data transfer from DB to HIVE etc ... Cons HIVE queries are comparatively slower than the native DB's such as mysql, snowflake or psql, meta data's and caching can be maintained to improve the performances Review Source VP Vidya P. Bidata engineer Information Technology and Services Used the software for: 2+ years ### "Hive is the goldmine for data enthusiasts" April 27, 2025 5.0 Overall Hive emerged as a great query engine with distributed processing and very capable for data analytics Pros Hive is a great capable data warehouse tool for data analysis and performing etl transformations at large scale Cons Hive processing is not very efficient in producing faster runs in line with other emerging tools like spark Review Source MD Mallikarjuna D. Lead consultant Information Technology and Services Used the software for: 6-12 months ### "Review on Apache Hive " September 12, 2020 3.0 I would strongly recommend to all to use and get an experience with this software Pros As a user I would pass some good things about hive it’s interface for Hadoop and it’s interfaces to different databases along with file system and we can integrate relation between file to file too Cons It’s very flexible and good at performance while load data from larger files and it’s good interface between homo and heterogeneous databases Review Source VR Verified Reviewer BigData Engineer Information Technology and Services Used the software for: 2+ years ### "A useful Data Warehouse for all the BigData enthusiasts" February 14, 2023 4.0 Basically you can store all the data that is structured in Hive built on top of Hadoop, that enables to store data easily and query them using SQL Pros It is simple to use as it really feels like a Database with its SQL like framework that easily parses queries behind the scenes into Mapreduce capable of supporting both internal and external data tables. It assins data to the machines in a cluster for faster performance with fault-tolerant capability to protect data at all cost. Cons Hive looks for data in the local machine and not HDFS, so there is no direct way to transfer files/data from local machine to HDFS (need to use external application). Execution time is not so fast as it takes a long time especially when there is a usage of joins in the queries as it relies on external disc space compared to Spark that uses in-memory space leading it to be more faster than hive. When hive is restarted, all the metadata gets erased. Review Source Diego S. Applied Data Scientist Marketing and Advertising Used the software for: 6-12 months ### "The Bigdata DatawareHouse that works seamlessly with Spark!!" June 21, 2021 5.0 Apache Hive has solved us the need of doing repetitive transformation over the final clean tables processed by our ETL process for all our analytical and business analytics tasks, now that we have the Data Warehouse in place we no longer have to extract summary extracts or perform any repetitive queries we did in the past, now we have designed a robust star schema with the main KPIs and calculations with all the look up tables we need and all without switching from technology or framework all in the same Apache Spark project!! Pros I love how easy is to integrate Apache Hive with Spark and perform SQL queries as if the tables were stored on Hadoop or S3 or GCP buckets. It is also very familiar to Spark users of tables stored on other file systems since it is based on the same storage (Hadoop HDFS) as regular Spark. And the best feature is that it is open source!! So, no extra cost for licensing!! Cons One thing is regarding its limitation of only being able to work with structured data and only being able to query tables, but for the regular use we do on our company it is more than enough (we do not have much unstructured data anyways). Review Source VR Verified Reviewer Data Specialist - Big Data and Analytics Information Technology and Services Used the software for: 2+ years ### "Apache Hive: Great for large scale batch workloads" January 13, 2021 5.0 Overall, I'm pleased with using Apache Hive for processing large big data workloads and recommends it for using batch processing. Pros Good for large scale ETL/ELT batch workloads SQL like syntax Good integration with Hadoop and Cloud technologies Ability to support customer UDFs High throughput and support for Spark. Tez and MR as an execution engine. Great support for different file formats (both row and columnar) Cons Not much support for data caching out of the box that results in larger processing time and high latency for interactive querying for data analysis. Review Source VR Verified Reviewer Consultant Computer Software Used the software for: 2+ years ### "Is Hive still relevant?" November 21, 2020 4.0 It's definitely better than writing map reduce code, but cloud based MPP solutions like BigQuery, Redshift and Snowflake do a much better job at making it easier to process big data with SQL. Pros Originally, Hive acted as an abstraction layer that translates SQL to map/reduce jobs. It still does this to this day, but it is also able to translate SQL to other engines that run on top of Hadoop. It also adds schema management on top of HDFS which, being the first schema management laysqer on top of HDFS, is used with other SQL on HDFS systems such as Presto, Impala and others. Cons The real problem is that in addition to learning Hive, you'd have to actually understand the underlying processing engines and how to tweak or tune them or what their obscure errors actually mean. Review Source VR Verified Reviewer System engineer Information Technology and Services Used the software for: 6-12 months ### "How apache hive can be used in bigdata nowadays." May 30, 2022 4.0 In hive i have worked in my organization for analysing the data and gives the graph chart to clients for taking the business decision. Based on the requirements we have made the graphical representation of data . Pros Hive is data warehouse where we can stores our data and perform analysis on that in larger scale. It gives superior scalability and flexibility for data analysis. hive data warehouse use cost effective. We can set timing to set up the duration of data warehouse on timing. So its a cost saving features while you use it for a larger scale data analysis.now hive mainly used in bigdata for managing large scale of data. Cons Hive is not ment for real time data analysis which is a big limitation for this warehouse.transaction processing data are not supported in hive data warehouse whice i feel its not ment for real time data analysis. Reason for choosing Apache Hive Its gives more scalability and it is cost effective. Review Source vamsi G. Sr ETL developer Computer Software Used the software for: 6-12 months ### "Review on Apache Hive" September 30, 2020 5.0 I would strongly recommend to users and colleagues to use at their product lines. Pros I am extensively using it for data querying, summarisation and analysis. I have used hive query’s to ingest the data into Hadoop framework. I am extensively used to pull the terabytes of data and generating the outbound files To external vendors. Cons It is very flexible to load the huge of amount of data and retrieval of the data also very fast. Since apache hive is the no sql, we have used multiple file systems to integrate and analyse the data. Review Source VR Verified Reviewer VP Financial Services Used the software for: 6-12 months ### "Great Way to query your Non-sql Data in a Sql Way!" October 10, 2020 4.0 Overall I just loved using Hive which integrates so well with Hadop and also Spark capabilities. Pros \- Integration with Hadoop/HDFS file system - SQL like querying capability makes it easy to query/group/slice data which is difficult to do using traditional map reduce programs Cons \- Little learning curve required in terms of loading the data from HDFS to tables, concept of external/managed tables, etc. Review Source VR Verified Reviewer Data Analytics Manager Logistics and Supply Chain Used the software for: 1-2 years ### "Reliable for big data processing but a bit outdated" June 20, 2022 4.0 We're able to rely on Hive for processing very large volumes of data. Pros Reliability has been the strongest aspect of Hive. In terms of capacity for processing large volumes of data, Hive gives us the best option when we're more concerned about success of our batch jobs than speed of execution. Cons Speed. Hive is a bit slower compared to other memory-based big data processing engines like Spark or Presto. Review Source VR Verified Reviewer Sr Statistician with Advanced Clinical Pharmaceuticals Used the software for: 6-12 months ### "Need to be good w sql" November 7, 2018 4.0 Decent, can do a good amt of data manipulation Pros Fast querying over big data. Programmable in a sense Cons Have to learn sql language to be able to use it Review Source VR Verified Reviewer Senior Technical Services Specialist Internet Used the software for: 2+ years ### "It will take some attempts, but it will push your big data around" October 3, 2018 4.0 Pros in proper configuration, great at querying and returning large data sets Cons Some restrictions that are tough to work around when coming at it from a mysql background Review Source RY Rajasekhar Y. Software developer Information Technology and Services Used the software for: 6-12 months ### "Review on Apache Hive " October 1, 2020 4.0 I would strongly recommend for others to use their projects for better performance and good experience Pros I’m using Apache hive for my current project based on my experience l would like write few good features about the software as its very sophisticated software for warehouse projects to providing data query and analysis and it gives SQL interfaces to query data stored in different databases . Cons Give us very faster for retrieving data and loading data .It’s being used for integrate file system integrated with Hadoop. Review Source SA Samuel A. Software Telecommunications Used the software for: Less than 6 months ### "Power of Big Data with SQL " May 19, 2023 5.0 Pros Apache Hive is a great tool that helps us work with a lot of data easily. It's very good at dealing with different kinds of data, both organized and messy. It uses SQL, a simple language most people already know, and can handle large amounts of data well. Cons Hive can be slow sometimes. It's not great for certain types of jobs like OLTP. There are also some problems with updating data and we could use better learning resources. Hive could also be better at dealing with data in real-time. Review Source PD Praveen D. Developer Computer & Network Security Used the software for: Less than 6 months ### "Hive review" September 30, 2020 4.0 Pros Very good product i would recommend one Cons Need more options and better controls for Review Source AH Akeel H. Student Used the software for: 6-12 months ### "Amazing for Big Data and Data Science enthusiasts" April 28, 2018 4.0 Pros Lets you scale unstructured data like it is structured data. Uses SQL like queries. Easy to use and program. Cons Does not provide enough support for analysis of big data. Mainly used for storage and retrieving tuples from data. 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