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Complete Guide to Azure VM: Pricing Models, Types & More

Trying to find the best virtual machine on the market that gives you the flexibility of easy scalability and the promise of a secure network – and doesn’t cost an arm and a leg (and maybe another arm)? Azure VM is likely the best solution for you… assuming you can project costs correctly. However, Azure doesn’t make it easy with its different offerings and pricing models.

Complete Azure SQL Pricing Guide

Azure Structured Query Language (SQL) has 18 different deployment options, service tiers, compute models, and two different pricing models: vCores and Database Transaction Units (DTU). Because of these complexities, it’s nearly impossible to project monthly budgets! This guide will explain the common Azure SQL pricing configurations and offer tips on optimizing your cloud budget.

Optimizing Space Technology: Fast Data Access with InfluxDB and Apache Parquet

To win the space race, aerospace and aviation companies must be fast. The end-to-end cycle of testing, visualizing test data, and making improvements demands swiftness, especially when a single launch yields billions of data points. It starts with real-time access to data. Real-time data analysis with nanosecond precision is crucial for monitoring environmental and habitat conditions when lives are at stake. Speeding up the iteration pipeline is essential but not sufficient. Cost efficiency matters too.

How to Design and Create Cloud-Native Applications for Data Analysis

Are you a data scientist, analyst, or IT professional seeking to leverage cloud computing for your data analysis projects? We understand your challenges in managing large datasets, scaling your analysis, and maintaining cost-effectiveness. This guide will walk you through designing and creating cloud-native applications for data analysis. By the end of this article, you'll have a clear roadmap for building robust, scalable, and efficient cloud-native data analysis applications that can transform your organization's data capabilities.

Integrating AI into Legal Workflows: Benefits and Challenges

Artificial Intelligence (AI) is rapidly transforming industries across the globe, and the legal sector is no exception. The integration of AI into legal workflows presents both opportunities and challenges for legal professionals. By automating routine tasks, improving decision-making processes, and enhancing efficiency, AI can significantly benefit legal teams. However, the adoption of AI also brings about challenges that must be carefully navigated. In this article, we will explore the benefits and challenges of integrating AI into legal workflows.

Empower Professionals to Perform Better with AI

Adopting cloud technology to gain velocity and agility in the marketplace allows companies to focus on what matters most. However, this transition isn't without its risks. In this episode of Data (R)evolution, hosts Janki Patel Westenberg and Francesco Tisiot are joined by Dave Li, former Senior Software Engineer at Helthjem, and Oded Valin, Co-Founder & CEO at EverSQL, to discuss the application of AI in database management, the importance of expertise in cloud adoption, and the need for streamlined tools in an increasingly data-driven world.

Event Streaming: The What, Why, and How

Event streaming is a powerful concept that has gained significant traction in the areas of data processing and real-time analytics. This post discusses the basics: what event streaming is, examples, and uses. Additionally, the post explores how to implement event streaming, as well as the technologies and tools involved.

InfluxDB 3.0 Product Update Round-up: Q2 2024

Wrapping up another quarter provides an ideal time to look back on the features we rolled out across various products. Software is never finished, and our engineers have been working hard to deliver improvements to InfluxDB 3.0. This roundup highlights some of the developments and releases over the last few months.

Why we used open source Apache projects to build InfluxDB 3.0

To the unfamiliar, building with open source tools may seem like the kind of chaos that leads to Boaty McBoatface-like decisions. Andrew Lamb, staff engineer at InfluxData and PMC for the Apache DataFusion project, provides insight from a developer and a PMC perspective about what it's like to build with, and manage a major open source project. InfluxData recently rebuilt its core database using Apache projects: Flight, DataFusion, Arrow, and Parquet, dubbed the FDAP stack.