Db2 vs. kdb+

The company has been using it for many years and I have been using it for just over 2 years. I feel the ease in obtaining the data. The solution can fit scenarios where there is quite a high workload and a low response time. Queries and transactions occur in milliseconds. Other backup/restore, replication and other features are fundamental and work exceptionally well. IBM is one of the most reliable companies and has been in the market for years in this segment and has helped us with support whenever we need it.

kdb is well suited for real time tick data and time series analytics.

• DB2 maintains itself very well. The Task Scheduler component of DB2 allows for statistics gathering and reorganization of indexes and tables without user interaction or without specific knowledge of cron or Windows Task Scheduler / Scheduled jobs.
• Its use of ASYNC, NEARSYNC, and SYNC HADR (High Availability Disaster Recovery ) models gives you a range of options for maintaining a very high uptime ratio. Failover from PRIMARY to SECONDARY becomes very easy with just a single command or windowed mouse click.
• Task Scheduler ( DB2 9.7 and earlier ) allows for jobs to be run within other jobs, and exit and error codes can define what other jobs are run. This allows for ease of maintenance without third party softwares.
• Tablespace usage and automatic storage help keep your data segmented while at rest, making partitioning easier.
• Ability to run commands via CLI (Command Line Interface) or via Control Center / Data Studio ( DB2 10.x+) makes administration a breeze.

• Time series analysis. The built-in vector operations are extremely fast. Also with the q language you can code up any customized analytical ideas quickly.
• The database are all file based, very easy to maintain.
• Very solid and fast interface to websocket, so you can interface with javascript easily.

• The relational model requires a rigid schema that does not necessarily fit with some types of modern development.
• Proprietary database, requires a lot of Hardware for its good performance and its costs are high.
• As data grows in production environment, it becomes slow.

• Run time error message readability, particularly for new users.
• Backwards compatibility between versions.

Since our services are running in IBM Kubernetes, using IBM Cloud Databases seem to be the best option. It may provide better performance than other vendors as everything is running in the same cloud. The overall experience so far is good as well.

switching costs

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.

its ok

Any issues related to DB2's availability are usually resolved easily and fast. We also have a team of dedicated analysts and admins to support the database technically. Once in a while we do request support from IBM for some complex issues that the on premise team can't resolve and the response is usually pretty fast and support is amazing!

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.

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.

We don't use it.

Db2 is one of the best relational databases I’ve used. It has the ability to maintain large amount of data and execution of million transactions in fraction of a second. If you use it properly, an organization can build a database with thousands of tables, and it can provide the exact information for the applications within a short amount of time

Python is very commonly used for large data analysis and in general is much easier to pickup than kdb+. The biggest drawback of kdb+ is the learning curve.

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!!

• Has reduced the downtime or outages due to HADR features which we lagged earlier.
• No manual intervention needed in most situation for us. IN worst case TSA does automatic failover so its transparent for the apps.
• LOB support is little bit problem for us now which we hope will have some improvement in product in future.

• It perfectly solves most of our real time tick data needs.
• Finding good kdb resources is slightly difficult. Also new people trying to learn kdb experience a relatively longer learning curve.