Db2 vs. Gemini Enterprise Agent Platform

I have primarily used it as the basis for a SIS - but I have migrated more than a few systems from there database systems to DB2 (Filemaker, MySQL, etc.). DB2 does have a better structural approach, as opposed to Filemaker, which allows for more data consistency, but this can also lead to an inflexibility that can sometimes be counterintuitive when attempting to compensate for the flexibility of the work environment as Schools tend to have an all in one approach.

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we used Vertex AI on our automation process the model very useful and working as expected we have implemented in our monitoring phase this very helpful our analysis part. real time response is very effective and actively provide detailed overview about our products.this phase is well suited in our org. this model could not applicable for small level projects why because this model not needed for small level projects and without related resource of ML this model not useful. strictly on non cloud org not suitable means on pram not suitable

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• While we query a large set of data, the results are generally available within a minute or so.
• Always reliable - I have never experienced an application going down.
• It is easy to write queries and find tables and columns.
• We can log in smoothly without any headaches.

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• Vertex AI comes with support for LOTs of LLMs out of the box
• MLOps tools are available that help to standardize operational aspects
• Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers

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• Learning curve for DB resources - Improvements to UI or native command line built-ins can help with increasing efficiencies for DB resources
• Better resource utilization monitoring and recommendations
• Continue to adopt support for modern frameworks and languages making it easier for organizations to see making Db2 the easy first choice

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• Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
• Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
• Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users

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The DB2 database is a solid option for our school. We have been on this journey now for 3-4 years so we are still adapting to what it can do. We will renew our use of DB2 because we don’t see. Major need to change. Also, changing a main database in a school environment is a major project, so we’ll avoid that if possible.

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You have to be well versed in using the technology, not only from a GUI interface but from a command line interface to successfully use this software to its fullest.

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I have never had DB2 go down unexpectedly. It just works solidly every day. When I look at the logs, sometimes DB2 has figured out there was a need to build an index. Instead of waiting for me to do it, the database automatically created the index for me. At my current company, we have had zero issues for the past 8 years. We have upgrade the server 3 times and upgraded the OS each time and the only thing we saw was that DB2 got better and faster. It is simply amazing.

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The performances are exceptional if you take care to maintain the database. It is a very powerful tool and at the same time very easy to use. In our installation, we expect a DB machine on the mainframe with access to the database through ODBC connectors directly from branch servers, with fabulous end users experience.

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Google is always top notch with their security and user interface performance. We use Google's entire suite in our business anyways, so using Vertex became second nature very quickly. I will say, though, that Google does need to come down on the price somewhat with their token allocation. Also, their UI is very robust, so it does require some time for training to really master it.

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Easily the best product support team. :) Whenever we have questions, they have answered those in a timely manner and we like how they go above and beyond to help.

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the material was very clear and all subjects have been handled

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db2 work well with the application, also the replication tool can keep it up

DB2 was more scalable and easily configurable than other products we evaluated and short listed in terms of functionality and pricing. IBM also had a good demo on premise and provided us a sandbox experience to test out and play with the product and DB2 at that time came out better than other similar products.

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We tend to adapt and use the platform that suits the customers needs the best. We return to Vertex AI because it is the most in-depth option out there so we can configure it any which way they want. However, it is not quick to market and constantly changing or updating it's feature-set. This makes it suitable for bigger customers that have the capital and time to spend on a bigger project that is well researched and not quick to market like some of the other options that feel like a light-version of this.

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By
using DB2 only to support my IzPCA activities, my knowledge here
is somewhat limited.

Anyway,
from what I was able to understand, DB2 is extremely scallable.

Maybe the information below could serve as an example of scalability.

Customer have an huge mainframe environment, 13x z15 CECs, around
80 LPARs, and maybe more than 50 Sysplexes (I am not totally sure about this
last figure...)

Today
we have 7 IzPCA
databases, each one in a distinct Syplex.

Plans
are underway to have, at the end, an small LPAR, with only one DB2 sub-system,
and with only one database, then transmit the data from a lot of other LPARs,
and then process all the data in this only one database.

The
IzPCA collect process (read the data received, manipulate it, and insert rows
in the tables) today is a huge process, demanding many elapsed
hours, and lots of CPU.

Almost
100% of the tables are PBR type, insert jobs run in parallel, but in 4 of the 7
database, it is a really a huge and long process.

Combining
the INSERTs loads from the 7 databases in only one will be impossible.......,,,,

But,
IzPCA recently introduced a new feature, called "Continuous
Collector".

By
using that feature, small amounts of data will be transmited to the central
LPAR at every 5 minutes (or even less), processed immediately,in
a short period of time, and with small use of CPU,
instead of one or two transmissions by day, of very large amounts of data and
the corresponding collect jobs occurring only once or twice a day, with long
elapsed times, and huge comsumption of CPU

I
suspect the total CPU seconds consumed will be more or less the same in
both cases, but in the new method it will occur in small bursts
many times a day!!

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• Negative: Difficult and manual deployment
• Negative: Missing assistants from common monitoring metrics
• Positive: Stability
• Positive: Performance
• Positive: Resiliency and high availability (HADR)
• Positive: Data Replication (Q-Rep)
• Positive: Interaction with storage subsystems for backups (TSM, SVC)
• Positive: Gigantic monitoring features in the form of table functions

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• It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
• It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
• It'll help you in terms of Security wherein we can use row level security access to authorized persons.

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