DB2 is a family of relational database software solutions offered by IBM. It includes standard Db2 and Db2 Warehouse editions, either deployable on-cloud, or on-premise.
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MongoDB Atlas
Score 8.6 out of 10
N/A
MongoDB Atlas is the company's automated managed cloud service, supplying automated deployment, provisioning and patching, and other features supporting database monitoring and optimization.
Vice President, Chief Architect, Development Manager and Software Engineer
Chose MongoDB Atlas
MongoDB is a great product but on premise deployments can be slow. So we turned to Atlas. We also looked at Redis Labs and we use Redis as our side cache for app servers. But we love using MongoDB Atlas for cloud deployments, especially for prototyping because we can get …
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.
I would recommend MongoDB Atlas to every company who have a significant need in the NoSQL database and do not want to manage their infrastructure. Using MongoDB Atlas can significantly reduce your management time and cost, which saves valuable resources for other tasks. It also suits a smaller company as MongoDB Atlas scales up and down very quickly.
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.
As an independent entity, MongoDB Atlas is not included in existing subscriptions from AWS or Azure, requiring an additional support plan and reliance on a third party.
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.
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.
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.
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 love MongoDB support and have great relationship with them. When we decided to go with MongoDB Atlas, they sent a team of 5 to our company to discuss the process of setting up a Mongo cluster and walked us through. when we have questions, we create a ticket and they will respond very quickly
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.
MongoDB Atlas has been in the market for very long time and there are bunch of documentation, training and support for it. It also is specifically designed for the use case similar to our project and big companies in the market uses them for very high load which made us confident about our choice.
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 withsmall 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 insmall bursts many times a day!!
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
