openHistorian
lambdo
Our great sponsors
| openHistorian | lambdo | |
|---|---|---|
| 15 | 3 | |
| 168 | 22 | |
| 1.2% | - | |
| 9.5 | 0.0 | |
| 18 days ago | over 3 years ago | |
| TypeScript | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
openHistorian
lambdo
-
Why isn't differential dataflow more popular?
It will return the sum of all values in column A. For large tables it will take some time to compute the result. Now assume we append a new record and want to get the new result. The traditional approach is execute this query again. A better approach is to process this new record only by adding its value in A to the result of the previous query. It is important in (stateful) stream processing.
Something similar is implemented in these libraries which however rely on a different data processing conception (alternative to map-reduce):
https://github.com/asavinov/prosto - Functions matter! No join-groupby, No map-reduce.
https://github.com/asavinov/lambdo - Feature engineering and machine learning: together at last!
-
Feature Processing in Go
I find this project quite interesting because sklearn has a good general design including data transformations and it does make sense to provide compatible functionality for Go.
Feature engineering in general is a hot topic and especially if features are not simple hard-coded transformations but rather can be learned from data. For example, I developed a toolkit intended for combining feature engineering and ML:
https://github.com/asavinov/lambdo - Feature engineering and machine learning: together at last!
What are some alternatives?
autotier - A passthrough FUSE filesystem that intelligently moves files between storage tiers based on frequency of use, file age, and tier fullness.
differential-dataflow - An implementation of differential dataflow using timely dataflow on Rust.
Kotori - A flexible data historian based on InfluxDB, Grafana, MQTT, and more. Free, open, simple.
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
questdb.io - The official QuestDB website, database documentation and blog.
rslint - A (WIP) Extremely fast JavaScript and TypeScript linter and Rust crate
awesome-TS-anomaly-detection - List of tools & datasets for anomaly detection on time-series data.
tablespoon - 🥄✨Time-series Benchmark methods that are Simple and Probabilistic
Spreads - Series and Panels for Real-time and Exploratory Analysis of Data Streams
sliding-window-aggregators - Reference implementations of sliding window aggregation algorithms
sktime - A unified framework for machine learning with time series
timely-dataflow - A modular implementation of timely dataflow in Rust