TDengine is an open source, high-performance, cloud native [time-series database](https://tdengine.com/tsdb/) optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. It enables efficient, real-time data ingestion, processing, and monitoring of TB and even PB scale data per day, generated by billions of sensors and data collectors. TDengine differentiates itself from other time-series databases with the following advantages:
- **[High Performance](https://tdengine.com/tdengine/high-performance-time-series-database/)**: TDengine is the only time-series database to solve the high cardinality issue to support billions of data collection points while out performing other time-series databases for data ingestion, querying and data compression.
- **[Simplified Solution](https://tdengine.com/tdengine/simplified-time-series-data-solution/)**: Through built-in caching, stream processing and data subscription features, TDengine provides a simplified solution for time-series data processing. It reduces system design complexity and operation costs significantly.
- **[Cloud Native](https://tdengine.com/tdengine/cloud-native-time-series-database/)**: Through native distributed design, sharding and partitioning, separation of compute and storage, RAFT, support for kubernetes deployment and full observability, TDengine is a cloud native Time-Series Database and can be deployed on public, private or hybrid clouds.
- **[Ease of Use](https://tdengine.com/tdengine/easy-time-series-data-platform/)**: For administrators, TDengine significantly reduces the effort to deploy and maintain. For developers, it provides a simple interface, simplified solution and seamless integrations for third party tools. For data users, it gives easy data access.
- **[Easy Data Analytics](https://tdengine.com/tdengine/time-series-data-analytics-made-easy/)**: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way.
- **[Open Source](https://tdengine.com/tdengine/open-source-time-series-database/)**: TDengine’s core modules, including cluster feature, are all available under open source licenses. It has gathered 19.9k stars on GitHub. There is an active developer community, and over 139k running instances worldwide.
For a full list of TDengine competitive advantages, please [check here](https://tdengine.com/tdengine/). The easiest way to experience TDengine is through [TDengine Cloud](https://cloud.tdengine.com).
For user manual, system design and architecture, please refer to [TDengine Documentation](https://docs.tdengine.com) ([TDengine 文档](https://docs.taosdata.com))
At the moment, TDengine server supports running on Linux/Windows/macOS systems. Any application can also choose the RESTful interface provided by taosAdapter to connect the taosd service . TDengine supports X64/ARM64 CPU, and it will support MIPS64, Alpha64, ARM32, RISC-V and other CPU architectures in the future. Right now we don't support build with cross-compiling environment.
You can choose to install through source code, [container](https://docs.tdengine.com/get-started/docker/), [installation package](https://docs.tdengine.com/get-started/package/) or [Kubernetes](https://docs.tdengine.com/deployment/k8s/). This quick guide only applies to installing from source.
TDengine provide a few useful tools such as taosBenchmark (was named taosdemo) and taosdump. They were part of TDengine. By default, TDengine compiling does not include taosTools. You can use `cmake .. -DBUILD_TOOLS=true` to make them be compiled with TDengine.
Note: Since snappy lacks pkg-config support (refer to [link](https://github.com/google/snappy/pull/86)), it leads a cmake prompt libsnappy not found. But snappy still works well.
TDengine includes a few components like taosAdapter developed by Go language. Please refer to golang.org official documentation for golang environment setup.
You can modify the file ~/.gitconfig to use ssh protocol instead of https for better download speed. You will need to upload ssh public key to GitHub first. Please refer to GitHub official documentation for detail.
[JDBC Connector](https://github.com/taosdata/taos-connector-jdbc), [Go Connector](https://github.com/taosdata/driver-go),[Python Connector](https://github.com/taosdata/taos-connector-python),[Node.js Connector](https://github.com/taosdata/taos-connector-node),[C# Connector](https://github.com/taosdata/taos-connector-dotnet) ,[Rust Connector](https://github.com/taosdata/taos-connector-rust) and [Grafana plugin](https://github.com/taosdata/grafanaplugin) has been moved to standalone repository.
Or, you can simply open a command window by clicking Windows Start -> "Visual Studio <2019|2017>" folder -> "x64 Native Tools Command Prompt for VS <2019|2017>" or "x86 Native Tools Command Prompt for VS <2019|2017>" depends what architecture your Windows is, then execute commands as follows:
Users can find more information about directories installed on the system in the [directory and files](https://docs.tdengine.com/reference/directory/) section.
Installing from source code will also configure service management for TDengine.Users can also choose to [install from packages](https://docs.tdengine.com/get-started/package/) for it.
Users can find more information about directories installed on the system in the [directory and files](https://docs.tdengine.com/reference/directory/) section.
Installing from source code will also configure service management for TDengine.Users can also choose to [install from packages](https://docs.tdengine.com/get-started/package/) for it.
To start the service after installation, double-click the /applications/TDengine to start the program, or in a terminal, use:
If you don't want to run TDengine as a service, you can run it in current shell. For example, to quickly start a TDengine server after building, run the command below in terminal: (We take Linux as an example, command on Windows will be `taosd.exe`)
TDengine provides abundant developing tools for users to develop on TDengine. Follow the links below to find your desired connectors and relevant documentation.