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InfluxDB is a widely used time-series database designed for storing and querying metrics, events, and telemetry data. It’s commonly used for infrastructure monitoring, application instrumentation, and IoT-style workloads where time-based data is central. In many environments, InfluxDB already exists as part of the monitoring or data collection pipeline, and the primary need is simply to visualize that data effectively.

TINYINT is one of the simplest numeric data types you can ever work with in SQL databases. It stores small numeric values, saves space, and is commonly used for flags, statuses, and boolean-like fields. But the moment you bring C# into the picture, things get intriguing. There is no TINYINT keyword in C#, and no one-to-one mapping you can use. Instead, you are left asking an important question: What is the correct C# equivalent of the TINYINT data type in SQL?

HubSpot Slack integration has become essential for the 238,000 companies on HubSpot and the 42 million users active on Slack each day. However, the native connector offers only limited functionality. Notifications often get buried, CRM updates remain locked inside HubSpot, and reporting still relies on manual exports. Worse, it lacks workflow customization and bidirectional updates leaving teams without the visibility and flexibility they need. This guide shows how to move past those limits.

How about ending this year on a major note? Enter dbForge 2025.3, our new release that covers the entire dbForge product line and brings lots of useful stuff to the table. This includes up-to-date connectivity options, a handful of UI/UX improvements, a wealth of newly supported syntax constructs, and a few more enhancements to make sure you start 2026 with your productivity at an all-time high. Without further ado, let’s take a look!

A time series database has a straightforward definition: it’s a database purpose-built for efficiently ingesting, storing, and querying time series data. Time series data is any data with a timestamp, collected regularly or periodically, that you’ll often visualize on graphs where the X-axis is time. This definition doesn’t quite tell you what sets it apart from other types of databases, though.

In the late 2000s, the big question in database design was SQL or NoSQL. While relational databases had long held their ground, document and key-value stores were emerging as serious alternatives. Many predicted a zero-sum, winner-take-all outcome. But when we look at how organizations are using database technologies today, no single tool or category has dominated the landscape.