Db2 vs. Google Cloud Datastore

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.

Incentivized

I feel like Google Cloud Datastore is well suited when the data models are simple and the possible filtering and sorting operation are not complex. With more complex filtering, the amount of required indexes increase, and so does the costs.

Incentivized

• 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.

Incentivized

• It is hosted in GCP, our primary cloud provider.
• It integrates with all the services we use in GCP.

Incentivized

• 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

Incentivized

• Part of the Google Cloud Platform walled garden.
• Pay for read/writes to the datastore, in addition to storage.
• Not many libraries exist.

Incentivized

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.

Incentivized

I give Google Cloud a full score because it satisfies our needs so well. We host most of our infrastructure on Google Cloud and using Google Cloud Datastore helps us to solve our NoSQL storage problem. and Google Cloud Datastore is so scalable and elastic. It saves us lots of time to maintain and saves us money.

Incentivized

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.

Incentivized

The simple implementation, together with the Google Cloud dashboard that allows data inspection, editing and querying, makes Google Cloud Datastore a comprehensive choice when it comes to NoSQL databases.

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

the material was very clear and all subjects have been handled

Incentivized

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.

Incentivized

If deploying an application in Google Cloud Platform, using Google Cloud Datastore is a no brainer because of the simplicity of setup. Other options would require more setup and configuration, and do not come with the same level of guaranteed uptime as Google Cloud Datastore. In our case, we've been using Google Cloud Datastore for 4 years without any issues and have never had to think about it.

Incentivized

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!!

Incentivized

• 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

Incentivized

• It solves our NoSQL database problem.
• It it highly scalable and available to meets our needs.

Incentivized