What Goes Around Comes Around... And Around...
Table Of Contents
This is an interesting paper I read last month. The notes on this paper gave me an idea of having linkblogs…
Some quotes
Under 4: Parting comments
ORMs are a vital tool for rapid prototyping. But they often sacrifice the ability to push logic into the DBMS in exchange for interoperability with multiple DBMSs. Developers fall back to writing explicit database queries to override the poor auto-generated queries. This is why using a RDBMS that supports SQL is the better choice.
Echoing my post on ORMs. epmhasis mine
The portion below, under the sections of blockchain is where things get personal…
Shots Fired for blockchains Ofcourse emphasis mine
We are required to place trust in several entities in today’s society. When one sells a house, they trust the title company to manage the transaction. The only applications without real-world trust are dark web interactions (e.g., money laundering). Legitimate businesses are unwilling to pay the performance price (about five orders of magnitude) to use a blockchain DBMS. If organizations trust each other, they can run a shared distributed DBMS more efficiently without wasting time with blockchains. To the best of our knowledge, all the major cryptocurrency exchanges run their businesses off traditional RDBMSs and not blockchain systems.
Blockchain proponents make additional meaningless claims of achieving data resiliency through replication in a peer-to-peer environment. No sensible company would rely on random participants on the Internet as the backup solution for mission-critical databases.
Essentially, Blockchain is a solution looking for a problem. And more ofthen than not, there are always better solutions then what Blockchain offers.
On ability to have a better onboarding DX.
One of the salient selling points of many non-relational DBMSs is a better “out-of-box” experience than RDBMSs. Most SQL systems require one first to create a database and then define their tables before they can load data. This is why data scientists use Python notebooks to analyze data files quickly. Every DBMS should, therefore, make it easy to perform in situ processing of local and cloudstorage files. DuckDB’s rising popularity is partly due to its ability to do this well. (My Note: Didn’t think about this till now…)