Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight. Data Lake Storage Gen2 extends Azure Blob Storage capabilities and is optimized for analytics workloads.
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PostgreSQL
Score 8.7 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.
Azure Data Lake is an absolutely essential piece of a modern data and analytics platform. Over the past 2 years, our usage of Azure Data Lake as a reporting source has continued to grow and far exceeds more traditional sources like MS SQL, Oracle, etc.
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.
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.
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.
Azure Data Lake Storage from a functionality perspective is a much easier solution to work with. It's implementation from Amazon EMR went smooth, and continued usage is definitely better. However, Amazon EMR was significantly cheaper overall between the high transaction fees and cost of storage due to growth. The two both have their advantages and disadvantages, but the functionality of Azure Data Lake Storage outweighed it's cost
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.
Instead of having separate pools of storage for data we are now operating on a single layer platform which has cut down on time spent on maintaining those separate pools.
We have had more of an ROI with the scalability as we are able to control costs of storage when need be.
We are able to operate in a more streamlined approach as we are able to stay within the Azure suite of products and integrate seamlessly with the rest of the applications in our cloud-based infrastructure
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.