Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
$0
capacity unit per hour
PostgreSQL
Score 8.5 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.
While evaluating Cassandra, PostgreSQL, MongoDB and DynamoDB we found Cassandra and DynamoDB being well suited for us. At the same time we didn't have the luxury of large team or devops so it came down to Amazon DynamoDB. As a small team we are glad to go forward with this …
We ended up selecting DynamoDB compared to similar products simply because we host on AWS. To use any other NoSQL solution would require more work in the long run due to having to maintain the EC2 instance, manage updates to the operating system and whatever NoSQL system that …
Main advantage of DynamoDB is Amazon's offering as SaaS. This removes the need for managing the database. DynamoDB is well suited for querying simple and flat JSON objects.
Compared to PostgresSQL, I would pick Postgres over Dynamo considering that Postgres is very mature and …
PostgreSQL provides both the traditional relational DB setup of MySQLand a more document-driven model like that of DynamoDB. As some of our data is relational and some is document-based, it was more efficient to select the tool that did both than run two, separate databases. …
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.
DynamoDB is a great service if you are looking for a quick and easy way to store NoSQL data in the cloud and do not want to be concerned with managing the server or infrastructure. If you are already invested in AWS, the value proposition is even higher as it works very well with the other services that AWS provides.
PostgreSQL, unlike other databases, is user-friendly and uses an open-source database. Ideal for relational databases, they can be accessed when speed and efficiency are required. It enables high-availability and disaster recovery replication from instance to instance. PostgreSQL can store data in a JSON format, including hashes, keys, and values. Multi-platform compatibility is also a big selling point. We could, however, use all the DBMS’s cores. While it works well in fast environments, it can be problematic in slower ones or cause multiple master replication.
The stability it offers, its speed of response and its resource management is excellent even in complex database environments and with low-resource machines.
The large amount of resources it has in addition to the many own and third-party tools that are compatible that make productivity greatly increase.
The adaptability in various environments, whether distributed or not, [is a] complete set of configuration options which allows to greatly customize the work configuration according to the needs that are required.
The excellent handling of referential and transactional integrity, its internal security scheme, the ease with which we can create backups are some of the strengths that can be mentioned.
The query syntax for JSON fields is unwieldy when you start getting into complex queries with many joins.
I wish there was a distinction (a flag) you could set for automated scripts vs working in the psql CLI, which would provide an 'Are you sure you want to do X?' type prompt if your query is likely to affect more than a certain number of rows. Especially on updates/deletes. Setting the flag in the headless(scripted) flow would disable the prompt.
Better documentation around JSON and Array aggregation, with more examples of how the data is transformed.
We will most likely continue to use DynamoDB for certain use-cases. If we stopped using DynamoDB as often, it would likely be because we started using Aurora Serverless more. Aurora Serverless may offer similar availability, management and cost benefits while allowing developers to use their MySQL tools and experience.
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.
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.
I have never contacted support for Amazon DynamoDB.
And I'm adding quite a lot of useless words to this explanation in order to reach the word count that is required despite the heading saying that I can skip this question. It seems there is then a bug here but what software does not have bugs?
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.
We evaluated using MongoDB or Amazon DyanmoDB. For us, the biggest advantage is that there's no maintenance cost for Amazon DynamoDB. Mongo gets complicated when you setup sharding. With Amazon DynamoDB, it's literally a push of button to increase throughput. This saves time and money on DevOps resources.
Postgres stacks up just [fine] along the other big players in the RDBMS world. It's very popular for a reason. It's very close to MySQL in terms of cost and features - I'd pick either solution and be just as happy. Compared to Oracle it is a MUCH cheaper solution that is just as usable.
Since the Amazon manages the instance, the amount of time a developer needs to spend configuring the database is less. For comparison, if we were to manage the same instance manually, we need to set up EC2 instance, install the DB, setup backup scripts, track backup failures, which is a great overhead for the dev. Using DynamoDB this overhead is reduced and hence having a great ROI.
Great documentation and easy setup makes an easy learning curve to transition to DynamoDB. Only caveat is as with any database, the data structure should be thoroughly analyzed for types of querying because there are limitations with the DynamoDB API.
Ties very well with rest of the Amazon eco system. Having rest of the applications in Amazon allows managing the application security a breeze.
The user-role system has saved us tons of time and thus money. As I mentioned in the "Use Case" section, Postgres is not only used by engineering but also finance to measure how much to charge customers and customer support to debug customer issues. Sure, it's not easy for non-technical employees to psql in and view raw tables, but it has saved engineering hundreds of man-hours that would have had to be spent on building equivalent tools to serve finance or customer support.
It provides incredibly trustworthy storage for wherever customer data dumped in. In our 6 years of Postgres existence, we have not lost a byte of customer data due to Postgres messing up a transaction or during the multiple times the hard-drives failed (thanks to ACID compliance!).
This is less significant, but Postgres is also quite easy to manage (unless you are going above and beyond to squeeze out every last bit of performance). There's not much to configure, and the out of the box settings are quite sane. That has saved us engineers lots of time that would have gone into Postgres administration.
