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Hive
4.2
(59)
by Hive Technology, Inc.
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Hive Reviews & Product Details

Hive Overview
What is Hive?

Hive is an all-in-one project management tool developed to “help teams move faster” regardless of how they work. Features are created based on users’ requests and are updated weekly, making Hive the world’s first democratic software platform. It’s best known for its capabilities in project management, time management, team collaboration, automation, and an array of integrations with third-party software. Hive is free to use for solo users and with premium versions available to teams and enterprises.

Company Hive Technology, Inc.
Year founded 2015
Company size 11-50 employees
Headquarters New York, NY, United States
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Capabilities
API
Segment
Small Business
Mid Market
Enterprise
Deployment Cloud / SaaS / Web-Based, Mobile Android, Mobile iPad, Mobile iPhone
Support 24/7 (Live rep), Chat, Email/Help Desk, FAQs/Forum, Knowledge Base, Phone Support
Training Documentation
Languages English
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Templates
Creation & Assignment
To-Do Lists
Recurring Tasks
Due Dates
Dependecies
Task Prioritization
Drag & Drop
Planning
Views
Project Map
Calendar View
Dashboards
Mass Updates
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Disclaimer
Our research is curated from diverse authoritative sources and meant to offer general advice. We don’t guarantee that our suggestions will work best for each use-case, so consider your unique needs when choosing products and services. Feel free to share your feedback.
Last updated: May 20, 2024
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59 Hive Reviews
4.2 out of 5
Enterprise (> 1000 emp.)
Jul 08, 2015
 Source
Overall Rating:
4.5
AG
Verified Reviewer
Share
"Used Hive for a Hadoop project"
What do you like best about Hive?

Hive has a simple and intuitive interface and gets the job done.

What do you dislike about Hive?

So far Hive has met and exceeded all my expectations.

What problems is Hive solving and how is that benefiting you?

Working on a Hadoop system to determine recruiters that are spamming members too much.

Small Business (50 or fewer emp.)
Apr 22, 2021
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"I am working on hive from last 2 years"
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

Enterprise (> 1000 emp.)
Jul 31, 2018
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"Hive gives you flexibility to query data in hadoop"
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.

Mid Market (51-1000 emp.)
Jan 10, 2018
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"Hive is useful but can be quirky"
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.

Mid Market (51-1000 emp.)
Jan 04, 2018
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"HIve Review - Data Science Perspective"
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.

Enterprise (> 1000 emp.)
Nov 27, 2017
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"TheHive"
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.

Mid Market (51-1000 emp.)
Nov 28, 2016
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"Excellent Batch Query Tool"
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.

What problems is Hive solving and how is that benefiting you?

Primary Querying engine for Data Analytics

Mid Market (51-1000 emp.)
Oct 25, 2016
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"Fast Queries for BI use cases"
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

Enterprise (> 1000 emp.)
Jul 08, 2015
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"SQL-like syntax makes it easy to use."
What do you like best about Hive?

The best part is being able to use a familiar syntax.

What do you dislike about Hive?

Doesn't support all MYSQL use-cases (understandably).

What problems is Hive solving and how is that benefiting you?

Ad-hoc queries on ETL'd production data.

Small Business (50 or fewer emp.)
Jul 08, 2015
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"Hive - Scalable Query Language for Hadoop"
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

Enterprise (> 1000 emp.)
Apr 29, 2015
 Source
Overall Rating:
4.0
AG
Verified Reviewer
Share
"Query Language for Hadoop"
What do you like best about Hive?

Hadoop does not have native query language, but Hive is a great addition to use on top of hadoop. I could point to a data stored in hadoop to a specific table and could use normal queries like I usually do in SQL. We can join and do aggregations etc. Makes life pretty simple.

What do you dislike about Hive?

It can be very slow as it runs on map reduce jobs underneath. Data cannot be updated but we will have to do a rewrite.

What problems is Hive solving and how is that benefiting you?

For people who are used to write SQL queries would have a very good time using Hive on top of hadoop for files stored in HDFS.

Enterprise (> 1000 emp.)
Dec 09, 2017
 Source
Overall Rating:
3.5
AG
Verified Reviewer
Share
"the hive - best in class tool "
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 .

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.

Mid Market (51-1000 emp.)
Mar 29, 2015
 Source
Overall Rating:
3.5
AG
Verified Reviewer
Share
"Hive makes query on HDFS much easier, but not optimized nor fast enough"
What do you like best about Hive?

Hive can tell us the detailed progress of a query, and can incorporate UDFs in different languages

What do you dislike about Hive?

The query speed is way to slow, and it does not support positional arguments in GROUP BY and ORDER BY

What problems is Hive solving and how is that benefiting you?

We use Hive to run our nightly workflows on HDFS in batch for data aggregation and analysis.

Enterprise (> 1000 emp.)
Jul 08, 2015
 Source
Overall Rating:
3.0
AG
Verified Reviewer
Share
"Great tool for quick analyses"
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.

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.