|influx||39.52 kB||MIT||10 Years||9 Feb 2022|
|influxdb-nodejs||16.79 kB||MIT||7 Years||8 Jun 2019|
|influent||67.31 kB||MIT||8 Years||19 Dec 2015|
|@influxdata/influxdb-client||283.12 kB||MIT||3 Years||23 Feb 2023|
|@sematext/logagent||227.24 kB||Apache-2.0||7 Years||25 May 2023|
|dogear||4.33 kB||MIT||7 Years||14 May 2020|
|artillery-plugin-influxdb||13.34 kB||Apache-2.0||7 Years||14 Jul 2017|
|influx-udp||7.72 kB||Apache-2.0||9 Years||29 Aug 2017|
|postgres-influx-mimic||149.83 kB||BSD||8 Years||18 Oct 2015|
|pastash||187.53 kB||Apache-2.0||6 Years||17 Dec 2019|
|influx-gateway||7.21 kB||MIT||8 Years||24 Feb 2016|
|delorean-influx||5.35 kB||9 Years||26 Jun 2014|
|influxdb-line-protocol||3.09 kB||MIT||8 Years||19 Jul 2015|
|influx4mqtt||3.68 kB||MIT||8 Years||7 Feb 2018|
|analytics-influxdb||3.65 kB||MIT||8 Years||24 Apr 2015|
Sure, here is the information in the requested Markdown format:
InfluxDB libraries are beneficial when you are working with time-series data and need a database platform explicitly built for this purpose. If your project involves monitoring, trending, or any time-based analytics, then the InfluxDB libraries provide you the right tools.
Typically, InfluxDB libraries provide the following functionalities:
Data Insertion: They offer functionality for writing large data sets efficiently and reliably to InfluxDB.
Management: They can manage aspects of an InfluxDB instance, including databases, users, and retention policies.
Data Validation: Most InfluxDB libraries also support data validation, ensuring data consistency and integrity.
When working with the InfluxDB libraries via npm, beware of the following pitfalls:
Version Compatibility: Make sure that the library you are using is compatible with the version of InfluxDB you have installed.
Async Operations: The nature of Node.js makes much of your interaction with InfluxDB asynchronous. You will need to handle promises and callbacks correctly to ensure the right order of operations.
Error Handling: Errors can arise due to numerous reasons like network issues, unavailable database etc. Proper error handling must be in place to ensure application resilience.
Memory Consumption: Inserting large amounts of data directly can lead to high memory consumption. Opt for batching or streaming data for efficiency.
Schema Design: Although InfluxDB is schema-less, a wrong data layout can degrade performance. Plan your tags and fields accurately.