Vertica BYOL, Red Hat
Micro Focus | 11.0.0-1Linux/Unix, Red Hat Enterprise Linux 7.5 - 64-bit Amazon Machine Image (AMI)
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The best integrated multitool for data storage and analytics
What do you like best?
What you usually expect from a storage solution is that it can save and provide comfortable access to all the data, not only for engineers but for plain users.
My experience with Vertica shows that it is a versatile and resilient tool, which provides a lot of fine-tuning knobs, but at the same time forgives the mistakes you make on data architecture design steps and at the same time motivates to incrementally enhance your solutions. A lot of integration capabilities, including Kafka, Spark and Hadoop, powerful security features.
It is also a software solution that makes it easy to scale up much easier than in appliance solutions.
My experience with Vertica shows that it is a versatile and resilient tool, which provides a lot of fine-tuning knobs, but at the same time forgives the mistakes you make on data architecture design steps and at the same time motivates to incrementally enhance your solutions. A lot of integration capabilities, including Kafka, Spark and Hadoop, powerful security features.
It is also a software solution that makes it easy to scale up much easier than in appliance solutions.
What do you dislike?
Several features are not (yet) presented in Vertica, which might be useful:
1. Procedures - not to process data or perform analytics, but to enhance SQL with DSL or common data access routines. It is particularly useful for DWH, when highly normalized layers require to have dynamically generated SQL to access.
2. Conditional execution. It will be handy for schemata management. With conditional execution, it is possible to define schema with idempotent change management.
3. Federative data access - sometimes it is much easier to just ask something in other databasess in real time, than to integrate it. Particularly useful for analytics.
Hope it will ve delivered some day.
1. Procedures - not to process data or perform analytics, but to enhance SQL with DSL or common data access routines. It is particularly useful for DWH, when highly normalized layers require to have dynamically generated SQL to access.
2. Conditional execution. It will be handy for schemata management. With conditional execution, it is possible to define schema with idempotent change management.
3. Federative data access - sometimes it is much easier to just ask something in other databasess in real time, than to integrate it. Particularly useful for analytics.
Hope it will ve delivered some day.
What problems are you solving with the product? What benefits have you realized?
Vertica is our primary tool for big data analytics (for structured data). Here's what we do:
- Ingest data from Kafka directly, and from other sources using Apache Nifi and Apache Airflow
- Create data pipelines for building cleaned and trustworthy datasets on user marts level
- Bulding detailed layer using modified anchor modeling approach
- Manage access to data via global role-model and unified data access policies
- Perform retention operations for old data partitions by moving it (again directly) to Hadoop
- Business analytics via Tableau
- ML models training and scoring, ad-hoc analytics and sandboxes
- CI/CD for schemata changes and versioning (using Gitlab)
All in all it is a tool that has a lot of applications in data management field.
And in most if the application cases it is not just "has capability", but does it on state-of-the-art level.
- Ingest data from Kafka directly, and from other sources using Apache Nifi and Apache Airflow
- Create data pipelines for building cleaned and trustworthy datasets on user marts level
- Bulding detailed layer using modified anchor modeling approach
- Manage access to data via global role-model and unified data access policies
- Perform retention operations for old data partitions by moving it (again directly) to Hadoop
- Business analytics via Tableau
- ML models training and scoring, ad-hoc analytics and sandboxes
- CI/CD for schemata changes and versioning (using Gitlab)
All in all it is a tool that has a lot of applications in data management field.
And in most if the application cases it is not just "has capability", but does it on state-of-the-art level.
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Long-term leader for big data analytics
What do you like best?
I most like the breadth of functionality that Vertica offers. For example, analytic lags and deltas and event pattern matching.
What do you dislike?
Whilst the documentation is generally good, I do manage to find and report back mistakes. It can sometimes take a while for these corrections to be incorporated into another documentation release.
What problems are you solving with the product? What benefits have you realized?
Log analysis and aggregation, complex KPI generation, and sessionisation of data. Using Vertica we have managed to combine data from a large number of sources and query it in one place.
Long time, happy Vertica customer
What do you like best?
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?
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 are you solving with the product? What benefits have you realized?
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!
easy analytics for everyone
What do you like best?
administrating vertica, extending vertica, ongoing development
What do you dislike?
poor performance on wide tables, missing predicate pushdown for custom source udf, missing ssl support for python udf, slow replication performance on load_snaphot with 10K+ tables in catalog, poor hash join performance comparing with greenplum or clickhouse
What problems are you solving with the product? What benefits have you realized?
product analytics, ab testing, operational analytics, preparing data for production services (moderation, antifraud, client reporting, ...)
Vertica Used By Netcore
What do you like best?
Speed and Response time, Easy to scale. Able to handle millions of records response in fictions of time.
What do you dislike?
Licensing Module, It Should be Pay As Use.
What problems are you solving with the product? What benefits have you realized?
Segmentation for the large number of records can be done in seconds. IT Support AWS S3, which saves lots of cost.
System Architecture Executive Manager
What do you like best?
High performance, high availability, low cost of maintenance
What do you dislike?
It would be nice to have a larger Vertica user community in Brasil
What problems are you solving with the product? What benefits have you realized?
We are using it as the main big-data repository for the results of the electricity market accounting process in Brasil. The performance provided by the platform allowed us to make data queries in hourly granularity available to our user base over the Internet.
Data engineer using vertica for database
What do you like best?
It Column-based analytical functions, this gives us the flexibility to work with massive data, and it makes our query fast and easy. Another point is its k-safety. It saves our data from any node failure
What do you dislike?
If we can say wrong about Vertica, then it's not good. Still, the area where Vertica can update itself is the connector for its clients
because when we use Vertica with a new version for spark like 3.0, then it has not better connectivity with Hadoop and spark. We have faced so many issues while connecting our spark application.
because when we use Vertica with a new version for spark like 3.0, then it has not better connectivity with Hadoop and spark. We have faced so many issues while connecting our spark application.
What problems are you solving with the product? What benefits have you realized?
We have created a Business intelligence tool for clients where we have to save massive data and process/query it very fast for a response. I think in this Vertica help's us a lot
Best analytics database in the Market.
What do you like best?
Dustributed computing , analytics functions. And It's continues improvement in the product. ML inside database improvement.
What do you dislike?
In enterprise mode lot of downtime required for node additions and rebalancing of large Database. To avoid this issue, EON mode architecture is suitable.
Update and delete statements are minus points in vertica due to these statements delete vectors will create. Lot of these statements will effect negatively on DB performance.
Update and delete statements are minus points in vertica due to these statements delete vectors will create. Lot of these statements will effect negatively on DB performance.
What problems are you solving with the product? What benefits have you realized?
It reduced lot of ETL jobs and user query runtime.
A great tool, if you are database person
What do you like best?
The setup of the environment, preloaded parts, gui of the tool
What do you dislike?
Some of the questions are more about exact values in the data rather than teoretical.
What problems are you solving with the product? What benefits have you realized?
I was doing the certification exam only
Vertica certification review
What do you like best?
Very insightful and learner-oriented videos. Excellent slides.
What do you dislike?
Sometimes the questions in knowledge checks were too technical and narrowed down to just finding the output of the code on the screen. I'd rather have more conceptual questions.
What problems are you solving with the product? What benefits have you realized?
I have gained a mass of new skills in database designing.
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