Table of Contents
Introduction
Compression methods
TDengine implementation
IntroductionIf the original data and decompressed data are exactly the same, the compression method can be considered lossless. A compression method that alters data is considered lossy.
Today TDengine Database , the open-source, cloud-native time-series database (TSDB) optimized for IoT, was named one of the Top 50 Most Promising Startups by tech sector-oriented media organization The Information.
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Average of time-series data stored in TDengine and visualized in Grafana
This is what the data looks like when visualized in Grafana. TDengine has a Grafana plugin, which allows you to easily visualize and monitor data.
The TDengine Server and Client can now be run on x64 systems that are running macOS, Windows 10 and 11, Windows Server 2016 and 2019, CentOS 7.9 and 8, or Ubuntu 18 and 20, as well as ARM64 systems running macOS or CentOS. For the latest information on operating system support, see the documentation.
Compression: Raw data is input into the compressor, which outputs compressed data.
Decompression: Compressed data is input into the compressor, decodes or In case you loved this informative article and you want to receive more information about
Tdengine time series database kindly visit the page. reconstructs it into raw data.
The purpose of compression is to represent the given data in as few bits as possible. In essence, this process trades compute time for storage space – while data compression enables more data to be stored on a storage medium, more compute resources are required to read and write compressed data. There is no single compression method or algorithm that is optimal for all data; instead, an appropriate method is chosen based on the characteristics of the data being compressed. Data compression is a summary of the trends and rules found in data. These rules can be based on content – the similarities between adjacent frames in a video, for example; on representation, as in entropy coding and transform coding; or on bitrate, as in differential compression and deep compression.
"I’m thrilled to see that TDengine has been selected as one of the most promising startups," said Jeff Tao, founder and core developer of TDengine. "This is another indication that industry insiders understand the potential of TDengine to power modern data workflows in IoT and other rapidly growing markets. I’m confident that TDengine is well positioned to continue making technical as well as business breakthroughs going forward."
With version 3.0.1.5, TDengine Database offers support for macOS in addition to Linux and Windows. You can now test your applications more efficiently and connect to a
TDengine Server running on any operating system from your own MacBook.
Losslessly compressed data can be completely reconstructed after decompression into the original raw data. This compression method is used in scenarios where data accuracy is important, such as compressing entire hard drives or compressing executable files. It may also be used for multimedia compression. However, lossless methods have relatively low compression ratios. Common lossless compression methods include differential coding, run-length encoding (RLE), Huffman coding, LZW compression, and arithmetic coding.
On the other hand, with lossy compression, the compressed data cannot be reconstructed into the original data – only into an approximation of that data. This compression method is used in scenarios where data accuracy is not important, such as compressing multimedia files. However, lossy compression enables high compression ratios. Common lossy compression methods include predictive codecs, fractal compression, wavelet compression, tdengine JPEG, and MPEG.
Compression methods
Commonly used compression methods for time series data are described as follows:
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Power BI is business intelligence and reporting software produced by Microsoft. With Power BI, you can import data and transform it to obtain the visual display that makes it easiest to understand. The main benefits of Power BI are as follows:
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In addition to these, TDengine also provides functions like STDDEV (standard deviation), MODE (the value with the highest frequency), and several other useful functions for basic and easy time-series analysis.
The one-stage compression is correspondingly compressed according to the type of data. The compression algorithms include delta-delta encoding, simple 8B method, zig-zag encoding, LZ4 and other algorithms, which we have briefly introduced above. Two-stage compression is based on one-stage compression, and then compresses with a general compression algorithm to ensure a higher compression rate.
The Top 50 Most Promising Startups is a yearly collection of up-and-coming enterprises in fields such as data, fintech, and cybersecurity that are considered by industry sources to have the most potential for future growth and valuation.