machbase-neo

✓ Performant timeseries database
✓ Scalable from Raspberry Pi to high-end servers
✓ Data transformation and visualization
✓ Data monitoring with dashboard
✓ Easy to install - instant download and run
✓ Easy to learn - familiar SQL with Tables and Columns
✓ Easy to write and query via HTTP, MQTT and gRPC
✓ Bridge to SQLite, PostgreSQL, MySQL, MSSQL, MQTT Broker, NATS

Get Started Download LATEST v8.0.38

Machbase is the world’s fastest timeseries database1 with a minimal footprint. It’s an ideal solution for environments that require scalability, from small servers with limited resources like the Raspberry Pi to horizontally scaled clusters. Machbase Neo, built on Machbase, adds crucial features required for the IoT industry. It ingests and handles query data through various protocols, such as MQTT for direct data transfer from IoT sensors, and SQL via HTTP for data retrieval by applications.

Download

Paste the script below into the shell prompt for the latest version of the platform.

sh -c "$(curl -fsSL https://docs.machbase.com/install.sh)"

If GUI is preferred rather than command line, then execute neow included in the Windows release.

Download the latest release for Windows

interfaces

Find and download the file for the version and platform from the releases page.

Data Visualization

Data transformation and visualization language TQL is supported out of the box.

  • TQL is the DSL for data transformation.
  • CHART() for the data visualization.
  • SCRIPT() for implementing custom logic.

Dashbaord

Realtime data monitoring on the fly.

API and Interfaces

  • HTTP : Applications and Sensors read/write data via HTTP REST API
  • MQTT : Sensors write data via MQTT protocol (MQTT v3.1.1 & v5)
  • gRPC : The first class API for extensions
  • SSH : Command line user interface via ssh
  • GUI : Web user interface

Bridges

Integration with external systems

  • SQLite
  • PostgreSQL
  • MySQL
  • MS-SQL
  • MQTT Broker
  • NATS Since v8.0.20
  • Kafka (planning)

Contributing

We welcome and encourage community contributions to documents and examples for other developers. Typo and broken link fixes are appreciated.

  1. TPCx-IoT Performance Results ↩︎

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