What users are saying about
81 Ratings
1 Rating
81 Ratings
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Score 7.9 out of 100
1 Rating
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Score 7 out of 100

Likelihood to Recommend

Apache Hive

Apache Hive shines for ad-hoc analysis and plugging into BI tools. Its SQL-like syntax allows for ease of use not for only for engineers but also for data analysts. Through our experience, there are probably more desirable tools to use if you are planning on integrating Hive into your processing pipeline.
Anonymous | TrustRadius Reviewer

MonetDB

MonetDB is great when you are performing adhoc queries on a large set of data. For example, if you store data in a typical RDBMS such as MySQL or Postgres and want to join large tables for analytics but the query runs unacceptably slow then MonetDB can act as a second database to offload complex queries. Based on my experience, it may not be a production-ready database since there aren't many DBAs familiar with it and due to lack of documentation, maintenance can become a little tricky.
Timothy Suh 서의선 | TrustRadius Reviewer

Pros

Apache Hive

  • Hive syntax is almost like SQL, so for someone already familiar with SQL it takes almost no effort to pick up Hive.
  • To be able to run map reduce jobs using json parsing and generate dynamic partitions in parquet file format.
  • Simplifies your experience with Hadoop especially for non-technical/coding partners.
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer

MonetDB

  • It performs very well with both a simple and complex query with multiple join operations.
  • It offers more advanced, enterprise level features such as clustering, data partitioning, and distributed query processing.
  • Loading bulk data is quite fast by taking advantage of multiple cores/CPUs.
Timothy Suh 서의선 | TrustRadius Reviewer

Cons

Apache Hive

  • Use Hive for analytical work loads. Write once and read many scenarios. Do not prefer updates and deletes.
  • Behind scenes Hive creates map reduce jobs. Hive performance is slow compared to Apache Spark.
  • Map reduce writes the intermediate outputs to dial whereas Spark operates in in-memory and uses DAG.
Anonymous | TrustRadius Reviewer

MonetDB

  • This is an open source software so there are obvious drawbacks, the biggest of which is a lack of documentation.
  • MonetDB does not seem to be well known outside of the academic environment so there is less information when you are searching for answers of any type.
  • I'd like to see more use cases and/or best practices so that commercial companies like ours can optimally use all of its highly performant features.
  • The code is written in C/C++ and this can be negative if you are a mainly java-shop and need UDF - User Defined Function.
Timothy Suh 서의선 | TrustRadius Reviewer

Likelihood to Renew

Apache Hive

Apache Hive 10.0
Based on 1 answer
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
Yinghua Hu | TrustRadius Reviewer

MonetDB

No score
No answers yet
No answers on this topic

Usability

Apache Hive

Apache Hive 8.5
Based on 9 answers
Thanks to its high usability Apache Hive enables users to craft extensive queries really efficiently and at the same time to how to hold response times very low. HiveQL simplicity makes it super easy to manage large datasets, what was almost an impossible task before introduction of Apache Hive data warehousing platform in our company.
Anonymous | TrustRadius Reviewer

MonetDB

No score
No answers yet
No answers on this topic

Support Rating

Apache Hive

Apache Hive 7.1
Based on 8 answers
Hive also has a community platform of its own just like other Hadoop frameworks. Most of the queries/problems are resolved in the community itself. We can just post our problems or get in touch with a specific user and get the issue resolved. Otherwise there is always the product support team for any resolution.
Partha Protim Pegu | TrustRadius Reviewer

MonetDB

No score
No answers yet
No answers on this topic

Alternatives Considered

Apache Hive

Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed.Amazon Redshift is the another product, I used in my recent organisation.Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
Manjeet Singh | TrustRadius Reviewer

MonetDB

There is a plethora of choices when it comes to NoSQL and columnar based databases. We use not one but sometimes 2 or 3 of them to carry out a specific purpose. We chose MonetDB because our engineering team enjoys working with open source software and appreciates its simplicity although becoming familiar with it did take time. I would not deploy MonetDB to production but it's a great backup option.
Timothy Suh 서의선 | TrustRadius Reviewer

Return on Investment

Apache Hive

  • It exposes the distributed calculation world (Hadoop) to the users but doesn't require the user to have the in-depth understanding of boilerplate details, it reduces the time of learning and let the data analyst can focus their efforts on the core business.
Anonymous | TrustRadius Reviewer

MonetDB

  • If you are familiar with a general database concept and played with open source products before then MonetDB will give you immediate return in terms of productivity since developers can quickly develop and verify their test cases involving back-end database with a large sample data set.
  • There is a stiff learning curve due to lack of documentation and sparse information available on the internet.
  • Overall experience has been positive since MonetDB gives you another option when it comes to building out a data warehouse.
Timothy Suh 서의선 | TrustRadius Reviewer

Pricing Details

Apache Hive

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

MonetDB

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

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