Exasol, from the company of the same name in Nuremberg, is presented by the vendor as a high-performance in-memory analytics database that aims to transform how organizations works with data, on-premises, in the cloud or both.
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PostgreSQL
Score 8.3 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.
Exasol is well suited for data warehousing, BI, ML, AI - all analytical queries. It has almost no operation cost, because it is selfmaintening the indexes etc.
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.
We have found Exasol to be very fast at summarizing large data sets. It has been a great backend for both reporting tools and data analytics/business intelligence. Combined with the fact that data import is also very fast it makes it ideal for a real-time ELT architecture.
Exasol is low maintenance. No indexes to maintain (The database auto-manages them) and very little tuning is required.
Query processing is optimized for high throughput and high parallelization. This means that even under high loads performance degrades gracefully as opposed to having "pile-ups" and "meltdowns". This has made it a very reliable database for us.
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.
I have had only positive experiences with their support. They are fast, knowledgeable, and courteous. Online support requests get picked up within hours. I've only once had to use their hotline and that was for an emergency. There was even one minor non-security bug report that I reported and which they fixed in the following week's minor release. I was quite impressed.
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.
We looked at some others too, but was 5 yrs ago so I don't recall the list. Exasol had the best performance per cost, outstanding performance, and was easy to evaluate. Even their community addition running on my laptop was faster than our existing reporting solution.
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.
