Microsoft SQL Server *

In the evolving landscape of database technology, choosing the right database management system is crucial for the efficiency and scalability of applications. This article presents a detailed comparison of the performance between Microsoft's CosmosDB and MS SQL Server. We'll examine how each database performs under various load conditions and share some interesting findings.

How do you deal with index fragmentation if your SQL server is working in high load environment with 24/7 workload without any maintenance window? What are the best practices for index rebuild and index reorganize? What is better? What is possible if you have only Standard Edition on some servers? But first, let's debunk few myths.

Myth 1. We use SSD (or super duper storage), so we should not care about the fragmentation. False. Index rebuild compactifies a table, with compression it makes it sometimes several times smaller, improving the cache hits ratio and overall performance (this happens even without compression).

Myth 2. Index rebuild shorten SSD lifespan. False. One extra write cycle is nothing for the modern SSDs. If your tempdb is on SSD/NVMe, it is under much harder stress than data disks.

Myth 3. On Enterprise Edition there is a good option: ONLINE=ON, so I just create a script with all tables and go ahead. False. There are tons of potential problems created by INDEX REBUILD even with ONLINE and RESUMABLE ON - so never run index rebuilds without controlling the process.

Finally, we will tackle the REBUILD vs REORGANIZE subject and what is possible to achieve if you have only Standard Edition.

When Alex Garland’s series Devs (on FX and Hulu) came out this year, it gave developers their own sexy Hollywood workup. Who knew that coders could get snarled into murder plots and love triangles just for designing machine learning programs? Or that their software would cause a philosophical crisis? Sure, the average day of a developer is more code writing than murder but what a thrill to author powerful new program.

In this article I want to show in detail how you can use R in Microsoft SQL Server to get data from Google Analytics (and generally from any API).

The task — we have MS SQL server and we want to receive data in DWH by API

We will use googleAnalyticsR package to connect to Google Analytics (GA).

This package is chosen as an example due to its popularity. You can use another package, for example: RGoogleAnalytic.
Approaches to problem solving will be the same.

In this article, I decided to describe how the functionality of selecting and displaying photos on a specific place on the map was implemented in our photo service gfranq.com. The photo service does not work now.

Since we had a lot of photos in our service and sending requests to database every time the viewport changes was too resource-intensive, it was logical to divide the map into several areas that contain information about the retrieved data. For obvious reasons, these areas have rectangular shape (although hexagonal grid was considered too). As the areas become more spherical at large scales, elements of spherical geometry and tools for it were also considered.

In this article, the following issues were raised:

• Storing and retrieving photos from the database and caching them on the server (SQL, C#, ASP.NET).
• Downloading necessary photos on the client side and saving them to the client cache (JavaScript).
• Recalculation of photos that must be hidden or shown when the viewport changes.
• Elements of spherical geometry.