Excellent bigdata warehouse solution
April 07, 2022

Excellent bigdata warehouse solution

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Apache Hive

Apache Hive is an open-source data warehouse solution built on top of Hadoop that helps to analyze a very large amount of data.
Our use case/scope is to work on a large data analytics project where the data frequency and velocity are very high. Apache Hive is very useful in processing both the unstructured and structured data in a seamless way. It help us in reducing to write complex queries as it is targeted to the SQL queries, we have a engineer team who are very proficient in writing SQL queries with the help of Apache Hive to process the big data.
We have identified no business issues using the solution.

  • Apache Hive supports external data tables.
  • Supports data partitioning to improve overall performance.
  • Apache hive is reliable and scalable solution.
  • Apache Hive supports writing ad-hoc queries as well.
  • Apache hive is not best suited for OLTP based jobs.
  • Sometimes we observed high latency rate while querying data.
  • Limitations on providing row-level data update.
  • Training materials needs improvements.
  • Apache Hive is a secured and reliable solution.
  • Using hive we can process the unstructured and structured data.
  • It reduces the complexity of writing high-level and complex MapReduce and simplify in writing the SQL scripts.
  • Provides query and data analysis in a summarised way that helps to understand by the end user.
  • Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
  • Apache hive can handle and process large amount of data in a sufficient time manner.
  • It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.

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Apache Hive is a data warehouse/ ETL solution that is being used for processing big data for analytics and visualizations. Apache Hive has great architecture that makes it very well suited for organizations.
The Metastore, is used for storing metadata for each table and its schema. The Driver operates as a controller for executions of the statements. Like other components such as Optimizer and CLI, Thrift Server are some components that enable the processing of big data transformation.