# Apache Parquet Reviews **Vendor:** The Apache Software Foundation **Category:** [Columnar Databases](https://www.g2.com/categories/columnar-databases) **Average Rating:** 4.3/5.0 **Total Reviews:** 27 ## About Apache Parquet Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language. ## Apache Parquet Reviews ### 1. A Game-Changer for Data Analytics **Rating:** 4.0/5.0 stars **Reviewed by:** Jasmine A. | Data Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** September 05, 2023 **What do you like best about Apache Parquet?** Apache Parquet has proven to be an invaluable tool in my data analytics toolbox. Its efficient columnar storage, cross-platform compatibility, schema evolution support, and performance optimization features have significantly improved my data processing tasks. It has not only enhanced my productivity but has also reduced infrastructure costs. I highly recommend Apache Parquet to anyone dealing with large datasets and seeking a robust, performance-driven storage solution.Apache Parquet has become an essential part of my data analytics toolkit, and I look forward to continued innovation and development in this fantastic open-source project. Kudos to the Parquet development team for creating such a powerful and user-friendly data storage format! **What do you dislike about Apache Parquet?** While Parquet does support schema evolution, it does add some complexity to the process, especially when dealing with complex schema changes. Schema evolution can require careful planning and management to ensure data consistency and query compatibility. **What problems is Apache Parquet solving and how is that benefiting you?** Apache Parquet for a wide range of purposes within the realm of data analytics, benefiting from its columnar storage, performance optimization, cross-platform compatibility, and support for evolving data schemas. It is a valuable asset for data analytics professionals aiming to unlock insights from large and complex datasets efficiently. ### 2. Apache Parquet forThe Modern Data Storage Format **Rating:** 5.0/5.0 stars **Reviewed by:** Vijay Paul G. | Senior Data Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** October 13, 2023 **What do you like best about Apache Parquet?** Compatibility is the best about the apache parquet, it is designed for the compatibility within a wide range of data processing of the frameworks and tools like apache spark, apache hive and apache impala and other tools that are helping in making its a one of the best choice **What do you dislike about Apache Parquet?** Though it is one of the best choice for batch processing it's doesn't supports real-time data storage **What problems is Apache Parquet solving and how is that benefiting you?** One thing parquet solving isthe columnar storage structure of parquet that allows for a quick query performance, it reads only the columns necessary for a query, it is great deal for the reducing I/O operations and improving the query speed ### 3. Best Big Data Manager **Rating:** 4.0/5.0 stars **Reviewed by:** Mayur D. | Mid-Market (51-1000 emp.) **Reviewed Date:** September 14, 2023 **What do you like best about Apache Parquet?** Best thing about Apache Parquet is that it is solving the storage requirements very efficiently. As far as I have experience it reduces the storage requirement by one third of data storage. And the parquet format base support might replace hadoop in future. **What do you dislike about Apache Parquet?** For now I don't specifically find anything as downside as I have just started exploring this now. But maybe in future I might have some suggestions on some features of this. **What problems is Apache Parquet solving and how is that benefiting you?** This will surely solve the problem which we face with hadoop. That is slowness in data retrival. And another is, as it supports Parquet file format so it can be easily used as replacement for various data lake storages. ### 4. It is like a subordinate which helping me all the time it help **Rating:** 4.5/5.0 stars **Reviewed by:** vipul t. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 21, 2023 **What do you like best about Apache Parquet?** It helps to store in columnar format and having schema evolution. It helps to convert data between avro and parquet formats. These files can be read and write by many programming languages **What do you dislike about Apache Parquet?** To be very Frank it is not compatible to handle small scale of data I am facing problems to encode and decode the data which effect my performance it also has limited support for complex data type **What problems is Apache Parquet solving and how is that benefiting you?** Handle the complex data and the feature which impress me at most is predicates pushdown which filter out the data which I required. It has campatible with many frameworks. ### 5. Highly efficient for use with big data processing frameworks **Rating:** 5.0/5.0 stars **Reviewed by:** Anzum B. | Software Engineer L59, Mid-Market (51-1000 emp.) **Reviewed Date:** November 15, 2023 **What do you like best about Apache Parquet?** It stores data in columnar storage which is highly efficient for analytical queries and also supports compression algorithms. It also has cross platform compatibility which makes it easy to integrate into existing data processing pipelines. **What do you dislike about Apache Parquet?** Write performance can be improved, and it taked some time to learn it **What problems is Apache Parquet solving and how is that benefiting you?** Making big data storage efficient by providing compression and retreival of data algorithms. Also helps in schema evolution and flexibility ### 6. Apache Parquet: A Versatile Data Storage Format with Some Considerations **Rating:** 4.5/5.0 stars **Reviewed by:** Pranshu G. | Software Developer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** September 04, 2023 **What do you like best about Apache Parquet?** One of Parquet’s key strengths is its compatibility with various data processing frameworks, including Apache Hive, Apache Spark, and Apache Drill. **What do you dislike about Apache Parquet?** However, there are some considerations to keep in mind when using Apache Parquet. While it excels in performance for read-heavy workloads, writing data into Parquet files can be slower compared to other formats like Apache ORC. **What problems is Apache Parquet solving and how is that benefiting you?** Apache Parquet solves storage and processing challenges by offering a highly efficient, flexible, and cross-platform data storage format. Its benefits include reduced storage costs, improved query performance, support for schema evolution, and compatibility with a wide range of data processing tools and environments. ### 7. Apache parquet for faster execution **Rating:** 4.0/5.0 stars **Reviewed by:** Nitish K. | Big Data Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** September 20, 2023 **What do you like best about Apache Parquet?** It is mostly useful for storing large amount of data that is used for bigdata analytics. Apache Parquet reduces IO operations, it is better compared to other tools **What do you dislike about Apache Parquet?** More complex to setup and maintain compared to rdbms like mysql **What problems is Apache Parquet solving and how is that benefiting you?** Parqued stores the data into the columns so the processing of the data is faster than any other traditional big data storage tools ### 8. Apache parquet for faster execution **Rating:** 5.0/5.0 stars **Reviewed by:** Ajay k. | Big Data Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** October 11, 2023 **What do you like best about Apache Parquet?** compression is the best fature of apache parquet as it delivers various compression techniques to reduce storage space and improve read performance. It also supports multiple compression algorithms **What do you dislike about Apache Parquet?** It doesnt support real time data ingestion, but its perfect choice for batch data processing **What problems is Apache Parquet solving and how is that benefiting you?** Apache prquet helps with my client's retail company related to saless,inventory,customer interactions and online shopping behaviour. This data is used for inventory optimization, sales forecasting and customer segmentation ### 9. Apache Parquet is superb **Rating:** 5.0/5.0 stars **Reviewed by:** Amruta J. | Software Test Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 18, 2023 **What do you like best about Apache Parquet?** Goods for storing any type of massive data, including texts, movies, photo's and structured data tables. It utilizes highly effective column wise comparison and customisable encoding algorithm **What do you dislike about Apache Parquet?** Using Apache Parquet having problems with lagre files. Higher CPU usage and affects query performance. Less efficient and can write data more slowly than row based formats like CSV. **What problems is Apache Parquet solving and how is that benefiting you?** By employing columnar storage, dictionary encoding, and run length encoding, Apache Parquet enhances data compression. Improving the compression ratios. Saves the values within the column ### 10. It's a best framework for development. Simple and easy implementation **Rating:** 4.0/5.0 stars **Reviewed by:** Ranjan D. | senior software engineer(network engineeering), Mid-Market (51-1000 emp.) **Reviewed Date:** September 04, 2023 **What do you like best about Apache Parquet?** Data compression and storage Storage for large amount of data and it's retrieval **What do you dislike about Apache Parquet?** Does not support json which is widely used for data exchange and transfer for cross platform and web development data exchange **What problems is Apache Parquet solving and how is that benefiting you?** Currently it's fine and need to see various data storage application as well ### 11. I prefer HBase over Parquet. **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** September 19, 2023 **What do you like best about Apache Parquet?** As it is free and open source so we use this and there are also some advantages of Apache parquet. Also it consumes very less space compared to its competitives. **What do you dislike about Apache Parquet?** As it is free and open source but still HBase is more popular and we in our organisation are using HBase. I am not criticizing but we people go for popularity and easa of usability. **What problems is Apache Parquet solving and how is that benefiting you?** We all know that it is a columnar file format and it is very high performance and efficient and also it comesums very less space and we mainly use it in big data ### 12. Exploring parquet **Rating:** 4.5/5.0 stars **Reviewed by:** Tanmay A. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 07, 2023 **What do you like best about Apache Parquet?** Best thing that I like about the parquet file format was compression and predictive push down that helps to select only those columns that needed not the whole data will come **What do you dislike about Apache Parquet?** The thing that we don't like for parquet files is that it does not support for the use case where our dataset schema frequently changing that pushes me use other file format **What problems is Apache Parquet solving and how is that benefiting you?** For me it benefiting by helps to store huge amount of data in compressed also easy and faster to query on large amount of data as I was using spark with it ,it support extermly good with spark ### 13. Apache Parquet : The Scalable Data Lake Architecture **Rating:** 4.0/5.0 stars **Reviewed by:** harshal s. | Small-Business (50 or fewer emp.) **Reviewed Date:** September 16, 2023 **What do you like best about Apache Parquet?** Faster execution of the query.Best compression technics which will help to reduce the storage. **What do you dislike about Apache Parquet?** As abatch processing system its not ideal for scenarios where we have to need real time updates. **What problems is Apache Parquet solving and how is that benefiting you?** We can store the large number of historical data. ### 14. Apache parquet and everything **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** September 08, 2023 **What do you like best about Apache Parquet?** Columnar storage, schema evolution, predicates pushdown, compression, compatibility across various data processing tools, supports wide range of data types like nested structures and arrays. **What do you dislike about Apache Parquet?** Limited use case since may not be used for transactional or operational data, overhead when reading or writing data due to its compression and encoding technique **What problems is Apache Parquet solving and how is that benefiting you?** Parquet stores data in columnar format which is sufficient for analytics, it improves query performance, allows schema evolution, supported in big data systems. ### 15. Best software for the large datasets **Rating:** 5.0/5.0 stars **Reviewed by:** Ankur Kumar R. | Analyst, Education Management, Mid-Market (51-1000 emp.) **Reviewed Date:** July 18, 2023 **What do you like best about Apache Parquet?** Apache Parquet is best solution for handling large datasets. It saves time and makes data loading easier than in JSON or CSV formats. **What do you dislike about Apache Parquet?** Need more schemas for different datasets. **What problems is Apache Parquet solving and how is that benefiting you?** It can be used on multiple query engines so that using diffferent engines becomes so easy. And by this data storage and retreival both are easy . ### 16. Revolutionary Columnar Storage **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** November 16, 2023 **What do you like best about Apache Parquet?** Performance and cross-platform compatible **What do you dislike about Apache Parquet?** Learning curve is quite steep, complexity is high **What problems is Apache Parquet solving and how is that benefiting you?** For big data analytics, and efficient storage of fata ### 17. Apache Parqut is the best db for columnar data storage **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** September 10, 2023 **What do you like best about Apache Parquet?** The best about Apce Parquet is it's ability to handle synchronisation and concurrent connections. It provides efficient data storage speed. **What do you dislike about Apache Parquet?** The daya retrieval speed for concurrent connections **What problems is Apache Parquet solving and how is that benefiting you?** It is making the db open source and that helps us see the operations done at there level to identify bottlenecks and improve ### 18. An efficient way to store columnar data **Rating:** 4.0/5.0 stars **Reviewed by:** Anuththara R. | Business Analyst Intern, Mid-Market (51-1000 emp.) **Reviewed Date:** June 19, 2019 **What do you like best about Apache Parquet?** I love the way it is created to store columnar data. The best thing i like most is that it is built to support very efficient compression and encoding schemes and can be used by anyone. And this is very much helpful in Big Data Analysis. **What do you dislike about Apache Parquet?** It was a bit hard to learn by myself but the Apache parquet site provides all the configurations in step by step procedures. So that was not a big issue with me. So honestly there is not much I dislike about it. **Recommendations to others considering Apache Parquet:** I would definitely recommend apache prequet to anyone if you are using columnar data processing in any project that you are working **What problems is Apache Parquet solving and how is that benefiting you?** In the hadoop project system that i have been i had to use compressed columnar data and there for the data processing frameworks Apache parquet helped me alot and made my work easier. ### 19. Pretty good software for large datasets **Rating:** 3.5/5.0 stars **Reviewed by:** Reeham N. | Lead Data Scientist/Analytics Manager, Investment Banking, Enterprise (> 1000 emp.) **Reviewed Date:** June 27, 2019 **What do you like best about Apache Parquet?** Certain times with various large datasets its difficult to process during an etl pipeline for hadoop. This makes it easier since connectivity to other platforms with parquet files is easier to command. It makes the data load easier to handle than json or csv. **What do you dislike about Apache Parquet?** There needs to be more schemas available for different business solutions. **Recommendations to others considering Apache Parquet:** Think about how your data looks like before committing as schemas are limited in growth. **What problems is Apache Parquet solving and how is that benefiting you?** Various types of load and compression as well as data loading within hadoop. ### 20. A great format for columnar data **Rating:** 3.5/5.0 stars **Reviewed by:** Jake B. | System Project Manager, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** March 18, 2019 **What do you like best about Apache Parquet?** I love how easy it is to use to store columnar data. Once you learn the details, it makes Hadoop-use a breeze. Column-store data has many benefits, and Parquet is such a help. **What do you dislike about Apache Parquet?** There is definitely a learning curve with the environment, but it is minimal. There honestly is not much I dislike about it. **Recommendations to others considering Apache Parquet:** I would definitely recommend Apache Parquet if you are considering using columnar-store data! **What problems is Apache Parquet solving and how is that benefiting you?** I had to gather raw data and consolidate it in a way to run statistical analysis and machine learning on it. Apache Parquet made my job a lot easier. This data analysis provided a huge step in the completion of the project. ### 21. Great **Rating:** 3.5/5.0 stars **Reviewed by:** Miah S. | Lead, Small-Business (50 or fewer emp.) **Reviewed Date:** June 19, 2019 **What do you like best about Apache Parquet?** Easy it is to use. Column-store data has many benefits. **What do you dislike about Apache Parquet?** Learning curve. It took a while to figure it out, but once I did it was great. **Recommendations to others considering Apache Parquet:** Stick through learning to use it. It’s great! **What problems is Apache Parquet solving and how is that benefiting you?** I would definitely recommend Apache Parquet if you are considering using columnar-store data! ### 22. Parquet is the Big Data solution **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** March 15, 2019 **What do you like best about Apache Parquet?** It is a widely adopted file format that works well with all big data applications. **What do you dislike about Apache Parquet?** I have no complaints about parquet. It's just a file format, much like CSVs. I guess one complaint is that you have to re-write your parquets to update their versions to get the latest parquet version benefits. **What problems is Apache Parquet solving and how is that benefiting you?** Big data analysis, ETL, etc. ### 23. Preferred storage format for hadoop **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** June 15, 2019 **What do you like best about Apache Parquet?** It's the best columnar storage forget we have used for our Hadoop system. **What do you dislike about Apache Parquet?** Not efficient for all of our cases. For entire routes we prefer avro. **What problems is Apache Parquet solving and how is that benefiting you?** Using our as an intermediate storage format in our application. ### 24. Parquet for data storage **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** May 15, 2019 **What do you like best about Apache Parquet?** Works with any table/data format we use. **What do you dislike about Apache Parquet?** Can be difficult to load from s3 when files get too big **What problems is Apache Parquet solving and how is that benefiting you?** Saving training data for our production models ### 25. Best storage format for big data **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Education Management | Mid-Market (51-1000 emp.) **Reviewed Date:** May 21, 2019 **What do you like best about Apache Parquet?** Parquet is parallel ready, and columnar in nature **What do you dislike about Apache Parquet?** libraries supporting parquet can be bit hard to find **What problems is Apache Parquet solving and how is that benefiting you?** Storing tbs of data ### 26. Well-designed format for your data needs **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Entertainment | Enterprise (> 1000 emp.) **Reviewed Date:** January 30, 2019 **What do you like best about Apache Parquet?** I am impressed at how well-designed the file format is. Best for big data/data analysis. **What do you dislike about Apache Parquet?** It's a high learning curve. You have to think about the benefits versus the drawbacks **What problems is Apache Parquet solving and how is that benefiting you?** Data analysis and machine learning. ### 27. Apache Parquet **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Education Management | Mid-Market (51-1000 emp.) **Reviewed Date:** June 01, 2018 **What do you like best about Apache Parquet?** The way the parquet-format project contain specifications format and properly formatted. **What do you dislike about Apache Parquet?** The complex nature of the database for a simple project. **What problems is Apache Parquet solving and how is that benefiting you?** Building Java resources that actually work. - [View Apache Parquet pricing details and edition comparison](https://www.g2.com/products/apache-parquet/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-11+21%3A47%3A39+-0500&secure%5Bsession_id%5D=aa2656ad-de54-45eb-9f68-0c0b0b2e015d&secure%5Btoken%5D=b89ee4e920fa36fd7751bc4cd332b7754a42ec582958cf7439c0eceb37ee555e&format=llm_user) ## Apache Parquet Features **Storage** - Data Model - Data Types **Availability** - Auto Sharding - Auto Recovery - Data Replication **Performance** - Integrated Cache **Security** - Role-Based Authorization - Authentication - Audit Logs - Encryption **Support** - Multi-Model - Operating Systems ## Top Apache Parquet Alternatives - [Azure Cosmos DB](https://www.g2.com/products/azure-cosmos-db/reviews) - 4.2/5.0 (59 reviews) - [ClickHouse](https://www.g2.com/products/clickhouse/reviews) - 4.5/5.0 (22 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,148 reviews)