Application of Time Series Database in Smart Electricity Utilization

Nowadays, daily life and enterprise production are inseparable from power equipment. Electricity consumption has become very common in our daily life, but you may not know that we also face with various risks when using electricity, such as the overload of power or the excess temperature of lines due to long-term use of electrical appliances. …

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CnosDB x LangChain: Querying Time-Series Databases with Conversational Interface

The topic of large models and related discussions has dominated the charts for over half a year. While discussing and paying attention to this, the CnosDB technical team has integrated large models and artificial intelligence-related technologies with database development and practices. Following the comprehensive integration of TensorFlow into CnosDB and the application of Copilot and …

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Time-series Database Market Outlook

The increasing urgency to rethink business, programs, investments, and strategies is driven by the shifts in the IT infrastructure, particularly in open source projects. Delving into the modern IT infrastructure, starting with the time series database that we are dedicated to, is an excellent way to kick off this journey. What is the Trend in …

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Dialpad: Ambition Goes Beyond $200 Million ARR

The COVID-19 pandemic has brought suffering to humanity but has also accelerated certain industries, including business communication. Business communication is shifting towards cloud-based phone systems. Nowadays, companies are increasingly turning to cloud-delivered solutions that combine a full range of communications such as phone, audio/video/web conferencing, messaging, and fax. Today, let’s take a look at a …

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Application of Time-series Database in Ship Risk Management

Advance in technology has led to ships being better equipped and crews being more knowledgeable, but the accident rate has increased. Domino theory suggests that a casualty does not occur as an isolated event, although an injury may occur suddenly at one moment, it is the result of a series of events occurring one after …

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Application of TSDB in the Civil Aircraft Industry

How high is the safety coefficient of a new aircraft? Is its performance consistent with the initial design? What aspects still need improvement? We can rely on extensive ground testing to find relevant answers, but the ultimate proof still depends on flight testing. For commercial aircraft manufacturers, flight testing is a core capability, and both …

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The Application of Time-series Database in Tabacco Manufacture

What is the most lucrative industry on earth — oil, gas or arms? The answer is none of the above. These industries are not the most profitable industries. The correct answer is tobacco. Today, at least 1/4 of the world’s people smoke, and cigarettes have become the ‘New currency’ of the world. The cost of …

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Dive into CnosDB 100,000 Lines of Source Code with Ease

Conquering Inaccessible Databases? CnosDB to the Rescue! Dive into 100,000 Lines of Source Code with Ease! Many members of our community have been curious about CnosDB and where to begin reading its source code. This question was discussed during a previous CnosDB HiTea livestream, and today we’ll revisit the topic. The CnosDB source code can …

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The Rise of Super Unicorn Databricks

Databricks, a leading super unicorn company, is revolutionizing the way businesses leverage data. With the explosive growth of internet data, data has become a new type of resource for businesses, as valuable as oil. More companies are looking to leverage various structured and unstructured data to gain a competitive edge.  However, they are facing challenges such as complex legacy infrastructure, resolving data silos, and managing high latency. Consequently, the demand for data lakes has been steadily increasing. A data lake is a storage repository that ingests vast amounts of raw data in its native format, enabling enterprises to easily access them when needed. Databricks is currently a super unicorn company in the primary market. It helps businesses prepare data for analysis, supports the adoption of machine learning, and enables data-driven decision-making. It also empowers data scientists to collaborate with data engineers and other …

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