Likelihood to Recommend I could think of a couple but the obvious is in Fintech and Retail, because of the amount of transactional and event level data for global operations. It is imperative to have a solution that can handle such large scale date, in real-time and batch delivery for inbound and outbound delivery, and ultimately ensuring that workload management is supported in some cases for around the clock SLAs.
Read full review Although Google Cloud SQL has room for improvement by addressing a minor lack of features, its features and services keep it high among other SQL database products. It is very fast compared to others. Since it is cloud-based, maintenance is also easier. Integration capabilities are also more than expected.
Read full review Pros 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. Read full review Highly scalable without worrying about sudden transaction explosion during peak hours. Highly available with multiple geographical locations and regions for nearly 0 downtime to the users. Extremely reliable and responsive for high latency applications due to superb networking at the core. Read full review Cons 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. Read full review Increasing support for more database engines may enable a wider range of application needs to be met. Implementing and updating cutting-edge security features on a constant basis. Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers. Read full review Likelihood to Renew 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.
Read full review Usability 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.
Read full review Google Cloud SQL is similar to the long existing conventional DBs like Oracle RDBMS, MS SQL Server in terms of usability and much more robust and easy to manage than them. Most of the commands are almost identical to these DB platforms and thus, easy to learn, understand and start using. Also, being highly available, it brings a sense of reliability with Google Cloud SQL.
Read full review Reliability and Availability 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.
Read full review Performance 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.
Read full review Support Rating 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.
Read full review GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.
Read full review In-Person Training the material was very clear and all subjects have been handled
Read full review Implementation Rating db2 work well with the application, also the replication tool can keep it up
Read full review Alternatives Considered 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.
Read full review Google SQL was great as a first SQL provision. It quickly enabled the apps to be built and scaled as needed for a while. It was robust and adaptable as needed and easy to export as needed when ready, depending on growth. Cost-wise, it's a good choice and requires little investment to get going.
Read full review Scalability 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!!
Read full review Return on Investment Fast response time by processing optimization and cost reduction by reduced CPU utilization. Nowadays, good performance is a necessary condition for the survival of a company and its sustained growth SQL enhancements are targeted to improve performance, simplify current and new applications, and reduce the development cycle time to market. A CPU reduction at peak times can immediately reduce our TCO by reducing software costs related to CPU utilization. Impressive reductions in memory requirements, which used to limit the concurrent database activity Out-of-the-box savings without changing the database or application Read full review With managed database system, it has given us near 100% data availability It has also improved web layer experience with faster processing and authentication using database fields Google Cloud SQL also gels up well with Google Analytics and other analytics systems for us to join up different data points and process them for deeper dives and analysis Read full review ScreenShots