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.
$0
MySQL
Score 8.3 out of 10
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MySQL is a popular open-source relational and embedded database, now owned by Oracle.
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Posit
Score 10.0 out of 10
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Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
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Pricing
Db2
MySQL
Posit
Editions & Modules
Db2 on Cloud Lite
$0
Db2 on Cloud Standard
$99
per month
Db2 Warehouse on Cloud Flex One
$898
per month
Db2 on Cloud Enterprise
$946
per month
Db2 Warehouse on Cloud Flex for AWS
2,957
per month
Db2 Warehouse on Cloud Flex
$3,451
per month
Db2 Warehouse on Cloud Flex Performance
13,651
per month
Db2 Warehouse on Cloud Flex Performance for AWS
13,651
per month
Db2 Standard Edition
Contact Sales
Db2 Advanced Edition
Contact Sales
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No answers on this topic
Offerings
Pricing Offerings
Db2
MySQL
Posit
Free Trial
Yes
No
Yes
Free/Freemium Version
Yes
No
Yes
Premium Consulting/Integration Services
Yes
No
No
Entry-level Setup Fee
Optional
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Db2
MySQL
Posit
Considered Multiple Products
Db2
Verified User
Analyst
Chose Db2
MySQL was definitely faster in terms of making queries, but DB2 had many features that protected against errors and easier to use for SQL beginners.
It's almost not comparable because they all do the same job in varying degrees. There are some things I like about Db2 that I don't enjoy about Oracle, but it mostly comes down to how it works and where it stores everything like SYS tables in Db2. MySQL is probably the fastest …
Before selecting Db2, I had the opportunity to work with three different products: MySQL, IBM API Connect and IBM Cloud Databases.MySQL is a very popular and effective relational database management system, especially known for its ease of use and reliability. While working …
I have experience with the above-mentioned similar products but mainly with MySQL. In terms of speed and query optimization capabilities, Db2 is far ahead in comparison to MySQL. Because of various issues like scalability, multiple departments hitting DB together causing …
It is faster and the transactions are much more safer and reliable if I compare it with the two SQL database I mentioned above, as far as MongoDB is concerned it completely depends upon the requirement of the project, if a SQL or a NoSQL database is more suitable for a project.
From working with other databases, I always felt that Db2 was at the top of its game in all aspects of performance, recoverability, and stability—pretty much everything you want out of an Enterprise database system.
IBM Db2 provides solutions for Data Lakes, Operational Databases, Data Warehouses, and Fast Data. IBM has a rich history of being a diversity, equity, and inclusion leader. Easy to design, implement, test, and implement with huge support material across different platforms. …
Considering Price, features configurations timelines of the IBM Db2 we found that is very Robust in Scalability, Reliability, Highly Available. also, we are already a IBM products user and we are much satisfied with the overall product as well as customer support from IBM team. …
Db2 is more scalable, reliable, and easily configurable than all the products that we evaluated. We were already using some of the services provided by IBM and were satisfied with the support and pricing. This led us to select Db2 as our database management system.
Db2 is one of the oldest and mature rdbms available in the market. IBM products were already been used in the organization. Cost effective in terms of licensing.
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 …
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 …
DB2 is much more robust than Oracle or mySQL when used in the Z/OS or Linux platform as it has the best error detection/warning system and also is very fast when accessed over the LAN in remote branch locations. It is scalable to a limited extent though as is the case in all …
I have managed Oracle databases too and in my opinion both the database platforms perform about equally. We mostly chose DB2 because we had existing resources familiar with DB2 and the DB2 platform was generally cheaper due to the ability to negotiate cheaper yearly license …
Postgres, SQL Server, DB2, Oracle, DashDB, MongoDB, RedShift - all of them have their strengths and weaknesses. I will say this about MySQL though, it is generally the first database chosen by a startup. It's easy to use, easy to deploy, free, and it just works.
MySQL is perceived as less scalable than DB2. DB2 provides for an easy migration up to more scale if it is acceptable or required to remain in the IBM ecosystem, which can scale all the way to z-Series mainframes. For some enterprises like insurance and banking, this is a …
We chose MySQL because of its open-source nature and its compatibility with various systems, languages, and databases. It is easy to use and fast. Additionally, it has been in the market for more than 30 years now which makes it a reliable option when compared to its …
Verified User
Consultant
Chose MySQL
it is cost effective solution and that time we were looking the good RDMS which can support the GIS based datatypes.
MySQL provides the option to reduce support and maintenance cost when P0 Level 1 support is not really needed for databases used for noncritical use cases and workloads. Other versions that include Microsoft SQL, Amazon RDS, etc don't provide such options and are overkill. …
The main reason that we went with MySQL is the cost. It's very cost effective and can do almost everything that Oracle can do. Database management is also very simple when compared to Oracle as we didn't have to contact the DBA for issues. Also, we found a lot of improvement in …
I have used more than 10 different SQL databases over the course of my career. Of those, the three I find myself using over and over include MySQL, Oracle and SQL Server. I have actually replaced smaller deployments of Oracle and SQL Server with MySQL as a way to reduce …
RStudio stacks up pretty well against Anaconda. However, Anaconda might be the first choice for someone who likes Python for their analytics and machine learning needs. In the past, I have found it seamless to connect Jupyter Notebook (in Anaconda suite) to integrate with other …
There are loads of people in the BI (Business Intelligence) space, of course... but I wouldn't touch any of them because none of them offer anything like the R and Python support that RStudio does. RStudio publishes open-source, they're a public benefit corporation, and they …
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.
MySQL is best suited for applications on platform like high-traffic content-driven websites, small-scale web apps, data warehouses which regards light analytical workloads. However its less suited for areas like enterprise data warehouse, OLAP cubes, large-scale reporting, applications requiring flexible or semi-structured data like event logging systems, product configurations, dynamic forms.
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.
Learning curve: is big. Newbies will face problems in understanding the platform initially. However, with plenty of online resources, one can easily find solutions to problems and learn on the go.
Backup and restore: MySQL is not very seamless. Although the data is never ruptured or missed, the process involved is not very much user-friendly. Maybe, a new command-line interface for only the backup-restore functionality shall be set up again to make this very important step much easier to perform and maintain.
Python integration is newer and still can be rough, especially with when using virtual environments.
RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
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.
For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.
There is no viable alternative right now. The toolset is good and the functionality is increasing with every release. It is backed by regular releases and ongoing development by the RStudio team. There is good engagement with RStudio directly when support is required. Also there's a strong and growing community of developers who provide additional support and sample code.
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 give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.
For someone who learns how to use the software and picks up on the "language" of R, it's very easy to use. For beginners, it can be hard and might require a course, as well as the appropriate statistical training to understand what packages to use and when
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.
RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses
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 have never contacted MySQL enterprise support team for any issues related to MySQL. This is because we have been using primarily the MySQL Server community edition and have been using the MySQL support forums for any questions and practical guidance that we needed before and during the technical implementations. Overall, the support community has been very helpful and allowed us to make the most out of the community edition.
Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.
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 has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant in the event of a DR or outage.
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.
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!!
RStudio is very scalable as a product. The issue I have is that it doesn't necessarily fit in nicely with the mainly Microsoft environment that everybody else is using. Having RStudio for us means dedicated servers and recruiting staff who know how to manage the environment. This isn't a fault of the product at all, it's just part of the data science landscape that we all have to put up with. Having said that RStudio is absolutely great for running on low spec servers and there are loads of options to handle concurrency, memory use, etc.
Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).
