Face-off in Cloud Data Warehouse Solution Reviews: HPE Vertica vs. Amazon Redshift vs. IBM dashDB

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For the Cloud Data Warehouse category at IT Central Station, key players dominate the top rankings;

While all three solutions have tie at an 8.0 average rating in our user community, what differentiates these softwares? What do they have in common? Do the softwares stand out among users for similar valuable features? Do users expect similar improvement areas among all three solutions, or does each solution have its own niche to beef up?

Enterprise tech professionals at IT Central Station talk about their experiences using Cloud Data Warehouse solutions, and shed light on valuable features and room for improvement that they’ve identified along the way.

HPE itcs
HPE Vertica

Valuable Features

HPE Vertica users at IT Central Station speak similarly of the software’s most valuable features, each of them signify the level of scalability that they’ve seen:

For SVP Data at Adform, Jochen Schlosser, HPE Vertica’s ad hoc data analysis is of top value — “it improved the SLAs for our end clients”, he writes.

As his advice for current or potential HPE Vertica users, Schlosser shares how and why his organization chose the software, “When we chose a solution, we were looking at scalability, maintenance, and ease of use. With Vertica, we can access big data using regular SQL queries.”

“High query performance…It provides the scale out capability by adding additional servers instead of scaling up the servers” explains DirectorSWDev284.

SoftwareDataArch072 explains that because Vertica’s compute and processing engine “returns the queries fast”, his team now has a way to better utilize their analysis resources.

Room for Improvement

Simultaneously, SoftwareDataArch072 raises several points of how HPE Vertica could be improved:

  • “Loading times for “real time” sources – for example, loading from Spark creates a load on the DB at high scale.
  • Connectors to other sources such as Kafka or AWS Kinesis.
  • Better monitoring tools.
  • Better integration with cloud providers – we were missing some documentation regarding running Vertica on AWS”

In addition, DirectorSWDev284 would like to see “integration with the latest Hadoop ecosystem.”
amazon redshift itcs

Amazon Redshift

Valuable Features

SeniorSo6b6f names a list of valuable features that he’s found in Amazon Redshift, particularly in its data management and integration capabilities, specifying:

Data Management

  • Processing huge data in petabytes
  • Massively Parallel Processing (MPP)
  • Concept of data compression
  • The way it stores the data in drives especially with the distribution key

Integration

  • Supports BI tools like MicroStrategy (MSTR) and Tableau
  • Supports all the data warehouse core features, such as SCD1 and SCD2, and different schemas like the star schema.

A BI Architect & Developer user of Amazon Redshift describes how using the software’s ‘column store’ feature grew his company’s user base to over 3,000, and how his team was able to rebuild their data warehouse from “scratch” to “current” within minutes.

Room for Improvement

As for improvements in the future, biarchit572622 “would like to see these RedShift features arrive in other languages, such as SQL’s ColumnStore index.”

ibmdashdb tcs
IBM dashDB

 

Valuable Features
Shailender Gupta calls IBM dashDB as a “high performance columnar database” that stores data at “10x compression in comparison to traditional RDMBS systems.”

By using IBM dashDB, he explains, his company “saves a lot of space on the cloud”, given their need to store and analyze has “large volumes of data (around 2-10 GB daily) in flat file formats and with high compression ratio.”

Gupta also speaks of the integrated RStudio feature that “makes using the product easy”, by functioning as a full scale database management studio (IBM Data Studio) and as a web-based management console.

For reviewer576447, “the cloud DBMS solution is most valuable”, adding that his company offers cloud data warehouse solutions on a “100% IBM stack.”

Room for Improvement

Gupta actually draws his own comparison to Amazon Redshift, arguing that unlike Amazon Redshift, IBM dashDB is not auto-scalable, and does not “allow you to add more storage and CPUs/instances without any significant downtime.”

For reviewer576447, “the support channels need to improve” and the documentation “is a bit tight.”

Curious to learn more about other Cloud Data Warehouse Solutions, as reviewed by real users IT Central Station?

Read our full collection of Cloud Data Warehouse Solution reviews.  

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