InterSystems Caché® was a multi-modal operational database for transaction processing applications, that provided several APIs to operate with same data simultaneously: key-value, relational, object, document, and multidimensional.
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PostgreSQL
Score 8.4 out of 10
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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.
Great for a one for all, heavy bundled, and licensed solution. When trying to evolve and scale, it can be very limiting. Think future proof as something that fits now could be hard to change later and work around.
PostgreSQL is ideal for handling databases that contain large volumes of information due to its efficiency, speed and above all because of the good management it makes of our resources, it also behaves very well in distributed environments of high demand, if you want a database of stable data and excellent performance PostgreSQL is one of the best.
The great functionality hides behind an old UI that can be cumbersome to navigate, making Cache configurations take more time.
The easy installs of Cache need specific setups to work well, and if yours is unique or if your servers are highly specialized on a networking level in terms of ports, VMs, or otherwise, then there may be some difficulties getting things to work.
The performance of PostgreSQL has been enhanced through the years, but always is better to have as much performance as we can.
The replication services could be done directly within the database, and more easily.
The Object Orientation of the Database could be extended, and albeit it manages inheritance of tables, and accepts XML and JSON as primary types, it would be wonderful if one could attach methods more easily to tables (to make them more like classes), and instances (rows for example).
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.
AWS, Heroku, and Digital Ocean all provide Postgres-as-a-service, where you pretty much never need to administrate it yourself but they do it for you. The Postgres community also has developed awesome and reasonably priced extensions, such as Citus DB and CockroachDB in case you need additional support for running it. If you need documentation, Postgres's docs are super thorough and their official forms are active.
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.
I've only worked with products that do one thing before, but there's so much that Cache offers versus piecing different services together manually. Not only does the product offer a more robust tool-set, but the support is wonderful and I've never encountered a better vendor in any industry in terms of how well they interact with their customers and care about helping you solve your problems. They want you to grow and to get better.
In this case, Postgres is preferred because it handles large data sets and requires fewer hardware resources than its competitor, MySQL. Compared to PostgreSQL, Microsoft products are excellent, but the installation process for MS SQL is lengthy. PostgreSQL has an advantage over its competitors in that it can adapt or configure third-party programs, applications, or settings.
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.
