Anonymous UserLead Data Analyst at a wholesaler/distributor
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"As long as you don't need to worry about the storage or cost, this solution would be one of the best ones on the market for scalability purposes."
"The most valuable features are the clustering, LS50, being able to change the size, the pay per use feature, the flexibility with many different sources and analytic applications."
"They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises."
"The initial setup is straightforward. You just need to follow the documentation."
"The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"I like the idea that you can assign roles and responsibilities, limiting access to data."
"The most valuable feature is the snapshot database. In one second, you can just take a snapshot of the database for test purposes."
"We chose Greenplum because of the architecture in terms of clustering databases and being able to have, or at least utilize the resources that are sitting on a database."
"Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible."
"The most valuable feature for us is horizontal scaling."
"Pivotal Greenplum's shared-nothing architecture."
"The parallel load features mean that Greenplum is capable of high-volume data loading in parallel to all of the cluster segments, which is really valuable."
"It's super easy to deploy and it also supports different languages and analytics."
"There are some stored procedures that we've had trouble with. The solution also needs to fine-tune the connectors to be able to connect into the system source."
"Support needs improvement, as it can take several days before you get some initial support."
"The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template."
"The solution could improve the user interface and add functionality to the system."
"Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway."
"They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in."
"If you go with one cloud provider, you can't switch."
"Availability is a problem."
"The installation is difficult and should be made easier."
"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."
"I saw some limitation with respect to the column store, and removing this would be an improvement."
"Initial setup is a little complex. It took around two weeks to deploy."
"The initial setup is somewhat complex and the out-of-the-box configuration requires optimization."
"They should add more analytics. Their documentation could also be improved so that I don't have to bother my co-workers and tech support so often."
"Pricing can be confusing for customers."
"The whole licensing system is based on credit points. You can also make a license agreement with the company so that you buy credit points and then you use them. What you do not use in one year can be carried over to the next year."
"You pay based on the data that you are storing in the data warehouse and there are no maintenance costs."
"It is not cheap."
"The pricing for Snowflake is competitive."
"On average, with the number of queries that we run, we pay approximately $200 USD per month."
"Pricing is approximately $US 50 per DB. Terabyte is around $US 50 per month."
"The price of Snowflake is very reasonable."
"We are using the open-source version of this solution."
Earn 20 points
Snowflake provides a data warehouse built for the cloud, delivering a solution capable of solving problems for which legacy, on-premises and cloud data platforms were not designed.
Parallel Postgres for enterprise analytics at scale
With improved transaction processing capability and support for streaming ingest, Greenplum can address workloads across a spectrum of analytic and operational contexts, from traditional business intelligence to deep learning.
Snowflake is ranked 1st in Data Warehouse with 27 reviews while VMware Tanzu Greenplum is ranked 8th in Data Warehouse with 6 reviews. Snowflake is rated 8.4, while VMware Tanzu Greenplum is rated 8.0. The top reviewer of Snowflake writes "Fast, convenient and requires almost no administration". On the other hand, the top reviewer of VMware Tanzu Greenplum writes "Powerful external data integration and parallel load capabilities, with good technical support". Snowflake is most compared with Microsoft Azure Synapse Analytics, Firebolt, Amazon Redshift, Teradata and AWS Lake Formation, whereas VMware Tanzu Greenplum is most compared with Apache Hadoop, Amazon Redshift, Teradata, Oracle Exadata and Vertica. See our Snowflake vs. VMware Tanzu Greenplum report.
See our list of best Data Warehouse vendors.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.