What users are saying about
70 Ratings
10 Ratings
70 Ratings
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Score 7.8 out of 100
10 Ratings
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Score 6.3 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

Presto

Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica
Praveen Murugesan | 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

Presto

  • Linking, embedding links and adding images is easy enough.
  • Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
  • Organizing & design is fairly simple with click & drag parameters.
Corinne Nacin-Martinez | 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

Presto

  • Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
  • Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
  • UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
Praveen Murugesan | 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

Presto

No score
No answers yet
No answers on this topic

Usability

Apache Hive

Apache Hive 9.0
Based on 1 answer
Hive's support SQL like queries improves its usability since almost every potential user of Hive would have had experience with SQL.
Tom Thomas | TrustRadius Reviewer

Presto

No score
No answers yet
No answers on this topic

Alternatives Considered

Apache Hive

I wasn't part of the evaluation process for Apache Hive. This was already implemented when I joined the company. I have worked with other big data plaftforms and I personally thinks most of them are quite comporable to one another. It really depends on what the company is going for. For exampel Google Cloud makes a ton of sense for a user if they developed their application on Google App Engine.
Sameer Gupta | TrustRadius Reviewer

Presto

Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
Corinne Nacin-Martinez | TrustRadius Reviewer

Return on Investment

Apache Hive

  • Hive Metastore is great as all other query engines plug into it. I'd tell the hive community to invest more into the metastore as it's one of the strong points of hive.
  • Overall, we first started with Hadoop, then Hive and then Presto. These are all core components of data in our business and it's highly critical for our business.
  • We use Hive extensively to compute daily/weekly reports which are essential to run the business.
Praveen Murugesan | TrustRadius Reviewer

Presto

  • Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
  • Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
  • Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.
Praveen Murugesan | TrustRadius Reviewer

Pricing Details

Apache Hive

General

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

Presto

General

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

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