Warp 10 is a modular open source platform that collects, stores and analyzes data from sensors. Shaped for the Internet of Things (IoT) with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database (TSDB) and a powerful analysis environment. The two components can be used together or independently. The Warp 10 Analytics Engine is based on a library of more than 1300 functions adapted to time series and on two analysis languages, WarpScript and FLoWS. This environment makes it possible in particular to perform statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter or Zeppelin. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system. Whatever your business, your data or your processes, Warp 10 fits your needs at any scale.
Based on our record, TimescaleDB seems to be more popular. It has been mentiond 5 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
(:alert: I work for Timescale :alert:) It's funny, we hear this more and more "we did some research and landed on Influx and ... Help it's confusing". We actually wrote an article about what we think, you can find it here: https://www.timescale.com/blog/what-influxdb-got-wrong/ As the QuestDB folks mentioned if you want a drop in replacement for Influx then they would be an option, it kinda sounds that's not what... - Source: Hacker News / 6 months ago
If you like PostgreSQL, I'd recommend starting with that. Additionally, you can try TimescaleDB (it's a PostgreSQL extension for time-series data with full SQL support) it has many features that are useful even on a small-scale, things like:. Source: over 1 year ago
I have built a Django server which serves up the JSON configuration, and I'd also like the server to store and render sensor graphs & event data for my Thing. In future, I'd probably use something like timescale.com as it is a database suited for this application. However right now I only have a handful of devices, and don't want to spend a lot of time configuring my back end when the Thing is my focus. So I'm... Source: over 2 years ago
I've seen a lot of benchmark results on timescale on the web but they all come from timescale.com so I just want to ask if those are accurate. Source: over 2 years ago
Ryan from Timescale here. We (TimescaleDB) just launched the second annual State of PostgreSQL survey, which asks developers across the globe about themselves, how they use PostgreSQL, their experiences with the community, and more. Source: about 3 years ago
InfluxData - Scalable datastore for metrics, events, and real-time analytics.
MetricsGraphics.js - D3-based library optimized for visualizing time-series data
Prometheus - An open-source systems monitoring and alerting toolkit.
QuestDB - QuestDB is the fastest open source time series database
OpenTSDB - OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase.
Quickmetrics - Here you'll find some handy helpers to send events to Quickmetrics. - Quickmetrics