Reporting has become faster and more cost-effective but data cleanup and writes still need work
What is our primary use case?
I used OpenText Analytics Database (Vertica) in my previous company for three years. The main use case was reporting. I worked for a fintech company that had a massive amount of data, and we had this use case for reporting, so we used OpenText Analytics Database (Vertica).
A specific example of how I used OpenText Analytics Database (Vertica) for reporting in my fintech company is that we had an ETL pipeline in which we processed the data and removed all PII and PCI data as part of the pipeline, then dumped all the data in S3. We used OpenText Analytics Database (Vertica) in Eon Mode, so the data was in S3 and we had compute nodes in AWS. We had a license from AWS Marketplace and were using the enterprise version. The consumers were the data analytics team, and our job was to make all the data available in OpenText Analytics Database (Vertica). In some use cases, we were creating projections to make queries faster because we had predictable reports to generate.
OpenText Analytics Database (Vertica) does not support good write, update, or insert queries, but from a read perspective, which was ideal for reporting, it has a strong use case.
What is most valuable?
The best features OpenText Analytics Database (Vertica) offers are that it is parallel, with Massively Parallel Processing (MPP), and it is a columnar database. It works in append-only mode, which is ideal for analytics and read queries. Additionally, I can use it in Eon Mode in which I can store the data in cheaper storage such as Amazon S3 and have different compute nodes. That helped me save costs. Beyond that, it is massively scalable, which was quite useful for our fintech use case. The read speed was excellent, and the data compression is good.
OpenText Analytics Database (Vertica) has positively impacted our organization by helping us reduce storage costs and improve reporting efficiency in our fintech company. The analytics team could run reports much faster, and we saved significant costs on compute and storage, especially with Eon mode and compression.
What needs improvement?
OpenText Analytics Database (Vertica) does not support hard delete, and they perform soft delete, which is the case with all columnar databases. If they could support or periodically clean up the data so that the data volume does not grow as much, that would be one suggestion. Beyond that, I think it is solid overall. Projections could be made more dynamic, and if they could find a faster way to update, insert, and delete data, that would also be helpful.
For how long have I used the solution?
I have been working in my current field for seven years.
What do I think about the stability of the solution?
OpenText Analytics Database (Vertica) is very stable. The migrations were smooth, we did not lose any data, and we only had to pause the pipeline.
What do I think about the scalability of the solution?
The scalability of OpenText Analytics Database (Vertica) is very strong. Being a columnar database, it scales quite well.
How are customer service and support?
Customer support for OpenText Analytics Database (Vertica) is excellent. We had multiple use cases because we moved from proof of concept to enterprise mode. We had to scale up OpenText Analytics Database (Vertica) and make some changes. Throughout this process, customer support was outstanding, and we had a person actively supporting us from the OpenText Analytics Database (Vertica) team for our use case.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I did not use any other solution before using OpenText Analytics Database (Vertica). Initially, this was the use case we had. We analyzed all the present tools and started with OpenText Analytics Database (Vertica) itself.
How was the initial setup?
For migration or upgrade to OpenText Analytics Database (Vertica), we were using three nodes and then shifted to five nodes based on the load. The migration was very smooth. We can take a backup in S3 and update it, so the compute part was stateless. The upgrade became very straightforward. Regarding metrics, the latency of the reports was very low, and we had many consumers because it was a B2B and B2C fintech company.
What was our ROI?
I have seen a return on investment with OpenText Analytics Database (Vertica). I saved a lot of money because the storage was on a cheaper alternative and was not directly on OpenText Analytics Database (Vertica), but on S3. I also saved time because setting up OpenText Analytics Database (Vertica) was a one-time effort, and the ETL pipeline was configured. We had different use cases for different reports, some of which were daily, some monthly, and some hourly. There I saved a lot of time, and the entire pipeline became automated. We benefited in terms of money, time, and employee resources.
What's my experience with pricing, setup cost, and licensing?
The pricing for OpenText Analytics Database (Vertica) is somewhat on the higher side for the license. Beyond that, the support from the OpenText Analytics Database (Vertica) team was very streamlined and excellent. We upgraded the OpenText Analytics Database (Vertica) cluster multiple times, and we always had a person supporting us from the OpenText Analytics Database (Vertica) team, so my experience was really strong.
Which other solutions did I evaluate?
Before choosing OpenText Analytics Database (Vertica), we evaluated other options such as Snowflake and others, but OpenText Analytics Database (Vertica) was the best for our use case because we wanted our data to be in our system. The support for S3 was also strong, and we had some expertise in OpenText Analytics Database (Vertica), as some team members were experts in it, so we started using it. We analyzed BigQuery and Snowflake.
What other advice do I have?
My advice to others looking into using OpenText Analytics Database (Vertica) is that if you want a read-heavy database and do not want it to be transactional in terms of write, delete, or insert operations, and if your use case is reporting, then OpenText Analytics Database (Vertica) is excellent for that use case. However, it is not ideal if you want to use it as a regular database, such as in e-commerce. If you want to use it in e-commerce, use it primarily for reporting. I would rate this product a 7 out of 10.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
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?
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.
