Hive Pros and Cons

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. Review collected by and hosted on G2.com.

Easy to load information and access. I have no dislike. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Higher latency is the drawback. Developments should be made to improve the latency of the complex queries. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

I don't have anything yet to state as a dislike I am satisfied in using hive Review collected by and hosted on G2.com.

Open source framework allows to read and write and manage tha data like sql , HQl which makes it easy to use. Review collected by and hosted on G2.com.

The latency in Apache hive is very high. Review collected by and hosted on G2.com.

Hive offer tool's for project planning, including the ability for track project and timeline, create and assign tasks and manage resources. Review collected by and hosted on G2.com.

I have no dislike towards hive since is the one I'm using Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Doesn't support OLTP and also doesn't support delete or update actions. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

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% Review collected by and hosted on G2.com.

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! Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Flexible and easy to understand loved it Review collected by and hosted on G2.com.

Not compatible with multiple platforms hence mostly plotform depend Review collected by and hosted on G2.com.