We use the solution for the warehouse. We implement machine-learning solutions such as clustering or classification models.
Vertica by the Hour, Red Hat
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Allows for a large amount of data to be stored with minimal physical space
What is our primary use case?
How has it helped my organization?
We can implement advanced solutions with very interesting capabilities to review whether the customer returns the tool and the licensing cost.
What is most valuable?
Vertica uses advanced Azure technologies to compress raw data using indexing, allowing a large amount of data to be stored with minimal physical space. Advanced algorithms are employed in data compression.
What needs improvement?
Pricing could be more competitive.
For how long have I used the solution?
I have been using Vertica for three years. We are using the V23 of the solution.
What do I think about the stability of the solution?
I rate the solution’s stability an eight out of ten.
What do I think about the scalability of the solution?
100-200 users are using this solution.
I rate the solution’s scalability a nine out of ten.
How are customer service and support?
Support is good.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup is straightforward. The deployment process includes creating a solar package to deploy this package on-premise or in a cloud environment. The solar package has all the configurations and components we need to implement as part of customer solutions. There are various software components requiring a specific configuration. So, we package this solar component and deploy it in the customer environment.
I rate the initial setup an eight out of ten, where one is difficult and ten is easy.
What's my experience with pricing, setup cost, and licensing?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What other advice do I have?
You can implement a cluster of servers, and we should guarantee high availability in a disaster recovery scenario. You can use Vertica in a production environment with distributed workflows and workloads. Vertica is available and has parallel processing and other capabilities.
You can implement a cluster of servers to guarantee high availability and massive parallel processing. It's a very sophisticated solution.
Vertica can be used to implement machine learning models such as classification, clustering, and aggregation models to support various use cases depending on customer needs. We have already implemented some machine learning models to detect anomalies. Some employees have distinct patterns in their working behaviors.
It is another feature-intelligent solution from OpenTex. It can implement or process structural data such as images, videos, text documents, and semi-structured data.
I recommend using this kind of solution because you can index your data and use a balancing algorithm to manage and retrieve data efficiently. Customers don't need a very large infrastructure to implement this type of solution. You can use it to implement advanced machine learning models, classification, and clustering. It also supports advanced artificial intelligence solutions.
Overall, I rate the solution a nine out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
Offers columnar storage and swapped partition features with impressive stability
What is our primary use case?
Our company uses one of the latest containerized versions of Vertica. When the curated processes are completed, our company uses Vertica at the end of all pipelines. In our organization, we usually store the curated datasets in parquet files, but we offer Vertica storage access for data consumers to manipulate and query the data easily. Our company also stores data in the Vertica database for analytics.
What is most valuable?
In one of our organization's prior investigation reports on Vertica, it was highlighted that the solution was executed quite quickly due to its columnar storage underground, which is the most valuable feature for our company.
What needs improvement?
Vertica is fast enough in data copying processes. The data digestion process is quickly completed using a certain copy command. The solution gets accelerated in processes if the queries are properly designed.
I have previously worked with Microsoft Secret Server and Deep Secure. I was familiar with the system's assets and transaction habits, so when I switched to Vertica, I had some expectations in terms of features from the other systems, which didn't quite match. The transactional operations and rollback were missing in Vertica, which I am trying to implement using the AUTOCOMMIT setting, but I am unsure whether the features will work according to my expectations.
For how long have I used the solution?
I have been using Vertica for three months.
What do I think about the stability of the solution?
I would rate the stability a nine out of ten.
What do I think about the scalability of the solution?
In our company, we have faced difficulties in scaling the solution for certain use cases. The solution didn't scale as expected in some cases, for which our company team witnessed performance issues. But in our company, we had doubts in the aforementioned cases if it was a query optimization or scaling problem. There are around 100 Vertica users in our organization. I would rate the scalability a seven out of ten.
How are customer service and support?
I would rate the technical support an eight out of ten.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I have previously used Redshift, MySQL, PostgreSQL and Microsoft Secret Server.
How was the initial setup?
When I was dealing with an onboarding task for the solution to implement a specific data pipeline with Vertica, I had to ideally and precisely configure the infrastructure and data architecture so that Vertica worked well enough in integration with Spark. If you have multiple systems and you want to establish communication between them, some drivers need to be provided, and some installations need to be made using JAR files.
For the deployment of Vertica, no client agents are required because it only involves passing the secret code to Vertica and executing the solution using Airflow DAGs, Vertica operators, Vertica hook and Spark solution, which work satisfyingly together. After processing datasets in our company, we store them in Vertica directly using Spark and Spark connector for Vertica. Our company uses Spark as a computational engine. Our company's operational team mainly takes care of Vertica's maintenance.
What's my experience with pricing, setup cost, and licensing?
It's an expensive product. I would rate the pricing a five out of ten.
What other advice do I have?
In one of the projects in our company, we dealt with a huge amount of customer data, and the configuration of this data was quite specific as it arrived from multiple business units. Our customers can have contact with different business units, and each unit is a company in itself. The same customer might pass, for example, one shopping mall of a business unit and might shift to another unit and identify themselves in both business units depending upon the identification process of how the data is collected.
The aforementioned project required identifying a unique user or customer with contacts with multiple business units and commercial centers. Our company processed a huge amount of the mentioned data type with the help of data science and machine learning models. Using the clustering process and leveraging the identified cluster users stored in the Vertica database, we executed some basic analytics on transactions involving customer spend, frequency of visits to a commercial center, and types of product selection.
I found the swapped partition of tables option to be extremely useful for our company which allowed me to perform some quick operations that would be otherwise impossible to guarantee the rollback in operations involving all assets. I would overall rate the solution an eight out of ten. I am unsure if my company would stick with Vertica in the future and it also depends on the vendor's promises on Vertica's scaling capacity.
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Review for OpenText Vertica
What do you like best about the product?
Opentext Vertica is a great platform to use for large data sets for data analysis and garher business insights
What do you dislike about the product?
OpenText has a lot of features to explore and it sometime lags while importing huge data set. Also, the pricepoint is a but on a higher side
What problems is the product solving and how is that benefiting you?
Processing data for me has become smooth and made the work on the job lot easier. With the useful insights I was able to present the data impactfully.
Great tool for business
What do you like best about the product?
The best thing about opentect vertica is that it provides great insight towards technology and solutions.
What do you dislike about the product?
Being a new user, a lot of these features confused me a little bit to choose one.
What problems is the product solving and how is that benefiting you?
Having huge data piling up opentext vertica helped me radicate that problem and helped me to process that data with ease.
Review for OpenText Vertica
What do you like best about the product?
OpenText helps in analyzing big data set easily and with high accuracy and gives valuable insights
What do you dislike about the product?
The pricing is on a higher side and has too many features that might get overwhelming.
What problems is the product solving and how is that benefiting you?
It is helpful in providing insights quickly which helped in presenting then to clients and coversion rate has substantially increased
Great tool for Ananlytics and Management
What do you like best about the product?
That it has broad set of analytical functions which reduces the operations part. Also , due to those features , it is very easy to implement and integrate in the business.
What do you dislike about the product?
That it is still limited to few features that other tools have.
What problems is the product solving and how is that benefiting you?
It is solving to deploy the lesser number of people in operations and data analytics part.
Streamlining work flow with OpenText Vertica
What do you like best about the product?
OpenText Vertica is flexible to do multiple tasks at a time and handles heavy loads of data processing with complex queries. The data lakes integrates multiple data sources enhancing the data analytics. The facility to add more clusters helps in handling huge tasks, better suits for large organizations.
What do you dislike about the product?
Implementing and integrating OpenText Vertica is quite complex. It requires good level of knowledge to work on tasks. Expensive in maintaining the system infrastructure hence doesn't fit for small businesses. The training documents and customer support could have been better.
What problems is the product solving and how is that benefiting you?
OpenText Vertica is very much helpful in building OLAP systems and data warehousing.Works efficiently in processing complex data with better data analytics. Improving the analytical capabilities and machine learning can extract valuable insights from large datasets. Brininging in more subscription plans with useful features covered in basic plans can benefit the users.
OpenText Vertica review
What do you like best about the product?
* Vertica is very fast. It works seemlessly with very large amount of data, it compresses the data very well.
* Vertica offers powerful built-in analytical tools for complexdata analysis. I have used this tool for marketing analysis.
* It is very easy to scale, we needed to scale up the nodes and it was done easily.
* Vertica offers powerful built-in analytical tools for complexdata analysis. I have used this tool for marketing analysis.
* It is very easy to scale, we needed to scale up the nodes and it was done easily.
What do you dislike about the product?
* For those who are not familiar with terminal usage, for them it's GUI feels outdated.
* Vertica struggles with petabyte-scale data, facing scalability challenges.
* It is a bit expensive for large data.
* Vertica struggles with petabyte-scale data, facing scalability challenges.
* It is a bit expensive for large data.
What problems is the product solving and how is that benefiting you?
Vertica is crucial for analyzing vast data volumes across business contexts. I have used it for internal data analysis, marketing outcomes and creating data marts for organisational insights. It efficiently handles large data ingestion, enhancing productivity.
Data analyst enthusiast with skills in data processing and warehousing
What do you like best about the product?
It has fastest query processing engine with ease to use UI. Scaleable in terms of storage and clsutering.
What do you dislike about the product?
It is Expensive with large data size and it faces difficulty to process greater than 100tb data size.
What problems is the product solving and how is that benefiting you?
It is better than Google Bigquery in terms of fastest processing and fells secure than liveramp safehaven analytical platform.
Good in handling High Performance
What do you like best about the product?
Handled high performance very efficiently.
What do you dislike about the product?
quite Expensive and sometime it lags in performance.
What problems is the product solving and how is that benefiting you?
I have used it to solve the high performance data.
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