Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.
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Db2
Score 8.6 out of 10
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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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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.
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 …
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 …
SQLite - Is the goto DB for Mobile/Desktop Apps. Its not as elaborate as Mysql but since its a RDBMS it provides all the basic features and its lite. We use mysql at the backend and for desktop app we use SQLite
postgres - Its a formidable opponent. It is fast and reliable and …
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 …
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
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.
Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
Learning curve around creation of broker and topics could be simplified
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.
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.
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
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.
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.
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
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.
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
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.
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!!
Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
Positive: it's scalable so we can develop small and scale for real-world scenarios
Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.