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Jeff Tao, Taos Data: Becoming the de-facto standard IoT big data platform

Jeff Tao, Taos Data: Becoming the de-facto standard IoT big data platform

Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.

Could you tell us a little bit about the company and what it offers?

TDengine builds innovative products to collect, store, compute, and analyze time-series data, based on the team’s deep understanding of the applications and characteristics of time-series data. Its flagship product TDengine is an open source time-series database with high performance, scalability and SQL support.

What are the main IoT big data trends you’re seeing at the moment?

With more and more devices internet connected, IoT data volume is growing exponentially. We need an efficient tool to store/analyze the data. Time-series data real time computing (forecasting and alert) will become a must-to-have feature in IoT data platform. 

As a relatively young startup how have you been establishing yourself in a market competing with larger companies that have been around for much longer?

TDengine stands out from other competitors by its hard core technology inside the product. Compared with other time-series databases, the key differentiations incorporated in the product are high performance, scalability and native SQL support. With these advantages, it cuts the total cost of ownerships of a IoT big data platform by at least 80%.

Why would developers choose TDengine rather than anything your competitors offer? What makes it stand out from the crowd?

Compared with other open source TSDBs, TDengine’s cluster feature is open sourced. Cluster feature is the key feature for IoT data platform since the system has to be scalable to meets the growing business and higher data volume. Most open source TSDBs do not support cluster. 

On the other hand, TDengine is a developer-friendly tool. Installation and cluster setup can be done in seconds. Its running status can be monitored via Grafana or other DevOps tools. The management cost to run a TDengine cluster is close to zero. In addition, it uses the most popular SQL as its query language instead of proprietary one like many other TSDBs. This feature reduces the learning and migration costs. At the mean time, TDengine supports SQL extensions to process time-series data better, and it provides the convenient and flexible schema-less data ingestion.

In summary, TDengine is a tool developed for developers and want to make developers successful.

Can you give us any practical examples of what companies or industries do with TDengine?

TDengine is widely used in many industries. For example, logistics company can store the fleet’s location data in TDengine and monitor the fleet’s movements. Clean energy power plants collects data from wind turbine, solar panel, those data can be saved into TDengine for real time analysis. Manufacturing always generates tons of data in the process, those data can be saved into TDengine for processing. All kinds of monitoring system (environment, IDC, servers, containers, etc) can use TDengine as its database.

Could you tell us a little bit about the TDengine Community Edition?

TDengine community edition is the open source edition, it has all the core features including cluster feature like the enterprise edition. Enterprise edition has more auxiliary features like securities, data encryption, GUI for management. 

The company raised $47 million in funding in May last year. How has that money been invested?

The raised funds are being used to attract more talent. Up until now, TDengine has more than 80 employees worldwide. We plan to hire more talent.  

What plans does the company have for the year ahead?

TDengine will have a new big release with richer features. Also, we want to promote it globally to have higher market penetration rate. Our long term goal is to make TDengine a de-facto standard for IoT big data platform.

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This UrIoTNews article is syndicated fromIoTTechNews

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