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
Score 8.8 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
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PostgreSQL
Score 8.7 out of 10
N/A
PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
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Pricing
Db2
MongoDB
PostgreSQL
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
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Db2 Advanced Edition
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Shared
$0
per month
Serverless
$0.10million reads
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Dedicated
$57
per month
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Pricing Offerings
Db2
MongoDB
PostgreSQL
Free Trial
Yes
Yes
No
Free/Freemium Version
Yes
Yes
No
Premium Consulting/Integration Services
Yes
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
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Community Pulse
Db2
MongoDB
PostgreSQL
Considered Multiple Products
Db2
Verified User
Engineer
Chose Db2
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.
Oracle and Microsoft are the ones that we have more to compare with and they are on par with Db2. postgres is the small solution that usually we leave behind and move to Db2. Mongo is the one that is different from what I used Db2 for but I know it has the capability to use …
We are underway to evaluate both, in their benefits versus concerns. One thing that makes IBM Db2 better is it is a very mature database with great performance
Db2 provides a combination of performance and scalability. Security wise, Db2 is always a first choice, especially for the systems where security can't be compromised. For mainframe systems, there is no other DB in the market that can perform better than Db2. If an organization …
Db2 has overall stronger capabilities with data maintenance, governance and task scheduling, however Teradata has a more developed online community with more robust and timely customer support. The support and training capabilities and the user community where you can interact …
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 …
Compared to similar products, Db2 shared common Relational DataBase Management System (RDBMS) features such as SQL support, data integrity, Atomicity, Consistency, Isolation and Durability (ACID) Compliance and concurrency control. However, the Db2 is designed for scalability, …
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.
We are working for our product , where we were using different database but that database was not fast our work So we switch to IBM Db2 for better result.
Verified User
Analyst
Chose Db2
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 …
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 …
Price aspect is good with DB2, db2 Blu as was disappointing it couldn't compete with IQ. pureScale was disappointing and couldn't compete with Oracle RAC. Pros of using db2 is that it is admin friendly. Also it has a lot of flexibility with memory management which other RDMs …
Looking into PostgreSQL happened post move to Mongo. Had we considered both options at the time we likely would have went with PostgreSQL. We may migrate at some point in the future but currently it doesn't make sense.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your …
Both Couchbase and MongoDB are document-oriented NoSQL databases, so they have very similar features. While they do have some fundamental differences in terms of how they scale, shard, etc. the one key reason why we went with MongoDB is its availability and support from the …
The flexible structure underlying MongoDB's construction is not found in other competitors; the ability to easily change the structure without affecting other stored documents. It is very ideal for projects that you cannot predict that the structure will change this way. Of …
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with Firebase. If you …
We tend to choose MongoDB when we're faced with a particular situation: we know that we need a NoSQL database in general, and want an open-source implementation that allows us to prevent against platform lock-in. Amazon's new DocumentDB product even allows us to choose to use …
MongoDB is the best NoSQL database out there. There are others, but Mongo has the largest community, is very easy to set up, and is extremely performant. Compared to a relational DB (like MySQL or Postgres) is like comparing apples and oranges. One isn't better or worse than …
I recently tried out Firestore from the Google firebase family of development products. While it allows structuring of data similar to MongoDB, it handles things a little differently. MongoDB documents are incredibly flexible and can be structured really any way you can …
MongoDB is my only NoSQL database that I have used. I have used SQL databases and don't find them as enjoyable. I code in full stack JavaScript and it blends perfectly with this. I know that there are competitors in this space, and I need to take time to try them all out. I …
I selected MongoDB because it works for well with web interfaces. All of the RDBMS alternatives would have required a lot more time writing schemas and working around retrieving data and mapping it. That could have been somewhat mitigated with Entity Framework, but that again …
The features between these database are quite comparable - except for possibly MongoDB. MongoDB being a different type of database and geared towards big data - I don't compare it to PostgreSQL. The other two I have used and would say PostgreSQL does fairly well when compared …
Despite being all open source options, what ended up making us choose PostgreSQL was the robustness of its core, which allows the great workflow that can support timely and efficient response to the demand and demand for resources. In the case of MongoDB, it is a non-relational …
MySQL is a popular open-source alternative to PostgreSQL, but in my experience it lacks the robustness, durability, and flexibility of PostgreSQL. It has also changed hands frequently, so support isn't the greatest. MongoDB and other NoSQL databases are helpful in certain …
First It's open source and it's cost-effective compared to other databases.PostgreSQL can be easily integrated with numerous platforms. It is well known and appreciated so relying on it as our system database can be easily accepted by our customers. And if your developing a …
PostgrPostgreSQL as a transaction db engine against oracle and sql server works well. TPM wise compared to MySQL and MariaDB, on an evan scale. SQL function supports, far outweighs compared to MySQL and MariaDB. PG Extensions allow for flexibiltity and scalability. Allows …
When we were originally evaluating Redshift we ran into some issue with dates. Either way, Postgres is a better choice than Redshift because it avoids vendor lockin. We ended up choosing Postgres over MySQL because it was easier at the time to get a hosted Postgres cluster up …
Much more mature and stable when compared to MySQL with features such as MVCC, complex subquery plans, ORDBMS, and NoSQL support. With Oracle retaining rights to MySQL its future as an open database is less secure and is no longer in the hands of the community. PostgreSQL also …
We selected PostgreSQL due to the number of employees who have used it in the past. The data consistency guarantees. The multiple transaction isolation levels support.
PostgreSQL outperforms every other option. It is faster, more flexible, more reliable, easier to maintain, and more consistent in behaviour than any of the other offerings.
It's a viable alternative, with a rich feature set and a reliable system. PostgreSQL is one of the best RDBMS's currently on the market in 2020, it serves just as well as a starter, PoC DB for any software idea as a final, highly valuable database solution for big systems.
PostgreSQL works better than MySQL for analytics workflows where a massively parallel processing database architecture is necessary. We used PostgreSQL because it allows better scalability for querying and data analysis compared to the transactional database MySQL that we use.
PostgreSQL is the proper tool when data consistency matters and other BASE or document-based databases are simply improper. I think PostgreSQL has a fantastic system of slony replication, triggers, and other data maintenance functionality that other databases generally don't …
Compared to MySQL, it works well if you need to extend to your use case Compared to Spark, it works better w.r.t development time in a central database setting Like Redis, it cannot be used for caching and quick access of non-structured data
As I said, Postgres and MySQL are open source which is important for small start ups. Oracle is EXPENSIVE :) Postgres is faster than MySQL (Big factor) MySQL supports replication which makes it more scalable.
I am currently using MySQL and it is difficult to notice much of a difference at all. For free relational databases, there hasn't been enough for me to choose a clear winner. If you're already using a free solution, there would be no reason to change. In terms of comparing to a …
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.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
PostgreSQL is best used for structured data, and best when following relational database design principles. I would not use PostgreSQL for large unstructured data such as video, images, sound files, xml documents, web-pages, especially if these files have their own highly variable, internal structure.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.
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.
The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.
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.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.
But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.
The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same family of applications that performs the company that develops it and that is not all bad, but being able to adapt or configure different programs, applications or other environments developed by third parties apart is what gives PostgreSQL a certain advantage and this diversification in the components that can be joined with it, is the reason why it is a great option to choose.
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!!
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.