Primary use case is advanced analytics over huge amounts of data. Vertica provides high speed access to high volumes.
Vertica by the Hour, Amazon Linux
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Scalable, high-speed database on commodity hardware
What do you like best about the product?
The ability to grow a database in either compute or storage with commodity hardware is very valuable. No other database comes to mind for speed of inserts or selects at this scale.
What do you dislike about the product?
The documentation has improved over the years but there is less information than some competitors. There aren't as many users of this database products compared to others so the community is somewhat lacking.
What problems is the product solving and how is that benefiting you?
Vertica solves the problem of storing petabytes worth of data while actually being able to join across datasets in a timely manner. This allows for discoveries that couldn't be made otherwise.
Vertica enables Cerner's Big Data Analytics
What do you like best about the product?
We are inserting 1B rows per hour now. This data is easily consumed by a mixed mode of users. It has enabled Cerner to conduct deep analytics across all of our technical stacks resulting in reduced client incidents.
What do you dislike about the product?
Hard to perform backups. If user pools are not continuously evaluated and monitored, large queries can bring the database to its knees. Still have not perfected a single node out situation. A single node out has put us into a downtime.
What problems is the product solving and how is that benefiting you?
Full analytics and visibility across our technical platforms. We have been able to do predictive fingerprinting and monitoring/auditing off of our data. We have approximately 1.1 PB of operational data used across multiple organizations.
Vertica is immensely useful for structured data
What do you like best about the product?
High amount of uptime
Clear documentation
Great python modules
Clear documentation
Great python modules
What do you dislike about the product?
I have no complaints about Vertica, but I do slightly prefer mysql due to syntax preferences
What problems is the product solving and how is that benefiting you?
Data analystics
Vertica in a League of its Own
What do you like best about the product?
Vertica query optimizer relies on up-to-date statistics for tables, schema, and the database. The statistics allow the optimizer to determine the most efficient plan to execute a query
What do you dislike about the product?
I am not able to change Profile data, Its saved in the pre made tables provided by creator.
What problems is the product solving and how is that benefiting you?
We are able to store more data, And customize that data into what we need.
Recommendations to others considering the product:
Quires can be made in any fashion as you need
SQL Functions, Each function is annotated with behavior type as immutable, stable or volatile.
SQL Functions, Each function is annotated with behavior type as immutable, stable or volatile.
Allows us to take volumes and process them at a very high speed
What is our primary use case?
How has it helped my organization?
Previous to Vertica, some analysis could not be made because of the amount of data needed. Vertica allowed us to take those volumes and process them at a very high speed.
What is most valuable?
Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data.
What needs improvement?
- Support is an area where it could get better.
- Promotion/marketing must be improved, even though it is a very useful product at very good price, it is not as "popular" as it should be.
For how long have I used the solution?
One to three years.
What do I think about the stability of the solution?
Just some issues with clustering, but they were not Vertica's issues.
What do I think about the scalability of the solution?
None.
How are customer service and support?
It could be improved.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I used Hadoop as the first approach. However, Vertica provided the best of both worlds (huge amounts of data and speed of access for analytics).
How was the initial setup?
Once you got your cluster setup and nodes properly working, it is very simple to set up Vertica.
What about the implementation team?
We did the implementation ourselves.
What was our ROI?
Huge. We are doing analytics that previously we could not.
Which other solutions did I evaluate?
We evaluated Exasol, but it came out to be too expensive for the use case.
What other advice do I have?
Do a good volumetric analysis to manage the storage needed.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Great product
What do you like best about the product?
HPE is one of the few solutions in their space that actually care about making an effective solution for their customers. Most companies just want the flashy new buzz words, but HPE prioritizes the real needs of their customers.
What do you dislike about the product?
There were no particular things I disliked
What problems is the product solving and how is that benefiting you?
Moved from Oracle to HPE Vertica, saved massive amounts of money on infrastructure and allowed us to scale.
Incredible
What do you like best about the product?
Before I met HP Vertica, I've worked with a few other column-store databases.
Few were easy to install and use, but were not reliable; others had good performance and stability but were definitely not use to deploy.
After 2-3 hours of deciding to try Vertica, I was running queries on it.
So what I like the best:
- Easy to deploy;
- Easy to Configure;
- Plenty of native tools to help the maintenance;
- Plenty of *clear* documentation to help you though;
- Fast - hands-down, the fastest for hardware I've worked with;
- Small - incredible compression rates to the data;
- Reliable/Stable fault-tolerant and - in my case - no data loss issues;
- No need for planning, analyzing or maintaining table indexes;
- Familiar way of loading data [PostgreSQL-like / COPY]
Few were easy to install and use, but were not reliable; others had good performance and stability but were definitely not use to deploy.
After 2-3 hours of deciding to try Vertica, I was running queries on it.
So what I like the best:
- Easy to deploy;
- Easy to Configure;
- Plenty of native tools to help the maintenance;
- Plenty of *clear* documentation to help you though;
- Fast - hands-down, the fastest for hardware I've worked with;
- Small - incredible compression rates to the data;
- Reliable/Stable fault-tolerant and - in my case - no data loss issues;
- No need for planning, analyzing or maintaining table indexes;
- Familiar way of loading data [PostgreSQL-like / COPY]
What do you dislike about the product?
Even though most of the problems I've had were already answered in public forums from the Vertica Communiy - I use the community version -, I feel like there's not a big crowd trying to help or at least trying to make their voice heard online.
What problems is the product solving and how is that benefiting you?
Using the Vertica Community Version, we were able to increase - sometimes by a factor of 10 - the speed of Data Warehouses queries.
As we didn't have much time to try tens of different databases, Vertica showed handy when it comes to Install/Loading data.
As we didn't have much time to try tens of different databases, Vertica showed handy when it comes to Install/Loading data.
Recommendations to others considering the product:
Read all the documents you can about Hardware Requirements. Even though it looks big, it's a very complete document, every DBA should beware of.
Because Vertica looks from outside a lot like PostgreSQL, users tend to forget some of its specificities when writing SQL queries or doing some other maintenance tasks. So beware of subqueries, data types, row-inserts - prefer bulk inserts - table/column drops, etc.
Because Vertica looks from outside a lot like PostgreSQL, users tend to forget some of its specificities when writing SQL queries or doing some other maintenance tasks. So beware of subqueries, data types, row-inserts - prefer bulk inserts - table/column drops, etc.
Long time, happy Vertica customer
What do you like best about the product?
Columnar storage makes for fast data access. Lots of storage on fewer nodes. Use of projections is an intuitive way to manage tables and help optimize queries. Great customer service, very responsive! Most importantly, they LISTEN to their customers! They are very responsive to problem inquiries, work closely with me and my fellow DBAs to figure out problem causes and solutions, and when an opportunity arises for a fix or an enhancement to the product, our combined solutions end up in the product for other users to benefit from! I have never had that experience with any other company.
What do you dislike about the product?
It has taken a while for Vertica to come up to speed on getting their product to fully take advantage of all the benefits the cloud (AWS, Azure, Google, etc) has to offer. But with their latest versions they are finally there!
What problems is the product solving and how is that benefiting you?
We have a wide and varied use of Vertica across the company. ETL/ELT processes, more intense reporting queries, and API queries requiring high concurrency and lightning fast response times. Vertica is able to handle all of it! We are moving data over from another data warehouse product as well, and are seeing query time reductions immediately, and exponential cost savings over the other product.
Recommendations to others considering the product:
Go through with a POC, it will open your eyes to the benefits Vertica will have on your system. And when working with competitors to do side by side comparisons, make them disclose what and how much hardware they are using to run the comparison queries against Vertica. It's not always apples to apples, and it is not always disclosed unless you ask!
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