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Posted to commits@streampipes.apache.org by ri...@apache.org on 2022/11/08 22:55:22 UTC
[incubator-streampipes] branch STREAMPIPES-622 created (now 8c61b006a)
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at 8c61b006a [STREAMPIPES-622] Modify README intro text, add animated screenshots
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[incubator-streampipes] 01/01: [STREAMPIPES-622] Modify README intro text, add animated screenshots
Posted by ri...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
riemer pushed a commit to branch STREAMPIPES-622
in repository https://gitbox.apache.org/repos/asf/incubator-streampipes.git
commit 8c61b006a9da7bca6e649d05298e890f79d8f943
Author: Dominik Riemer <do...@gmail.com>
AuthorDate: Tue Nov 8 23:55:09 2022 +0100
[STREAMPIPES-622] Modify README intro text, add animated screenshots
---
README.md | 64 ++++++++++++++++++++++-------------
images/streampipes-connect.gif | Bin 0 -> 949971 bytes
images/streampipes-data-explorer.gif | Bin 0 -> 543486 bytes
images/streampipes-pipelines.gif | Bin 0 -> 1296806 bytes
4 files changed, 41 insertions(+), 23 deletions(-)
diff --git a/README.md b/README.md
index b054d0ad7..bb53b65e1 100644
--- a/README.md
+++ b/README.md
@@ -23,6 +23,8 @@
[]()
[](https://twitter.com/StreamPipes)
[](https://dashboard.cypress.io/projects/q1jdu2/runs)
+[](https://github.com/apache/incubator-streampipes/graphs/contributors)
+
<h1 align="center">
<br>
@@ -33,9 +35,6 @@
<h3 align="center">Self-Service Data Analytics for the (Industrial) IoT</h3>
<h4 align="center">StreamPipes is a self-service (Industrial) IoT toolbox to enable non-technical users to connect
, analyze and explore IoT data streams. </h4>
-<p align="center">
- <img src="https://streampipes.apache.org/img/screenshots/streampipes-overview.png" alt="StreamPipes Pipeline
- Editor"/>
</p>
***
@@ -43,8 +42,9 @@
## Table of contents
* [About Apache StreamPipes](#about-apache-streampipes)
- * [Use Cases](#use-cases)
+ * [User interface](#userinterface)
* [Installation](#installation)
+ * [Documentation](#documentation)
* [Building StreamPipes](#building-streampipes)
* [Pipeline Elements](#pipeline-elements)
* [Extending StreamPipes](#extending-streampipes)
@@ -58,30 +58,42 @@
## About Apache StreamPipes
-Apache StreamPipes (incubating) enables flexible modeling of stream processing pipelines by providing a graphical
-modeling editor on top of existing stream processing frameworks.
+Apache StreamPipes (incubating) makes industrial data analytics easy!
-It empowers non-technical users to quickly define and execute processing pipelines based on an easily extensible
-toolbox of data sources, data processors and data sinks. StreamPipes has an exchangeable runtime execution layer and
-executes pipelines using one of the provided wrappers, e.g., standalone or distributed in Apache Flink.
+StreamPipes is an end-to-end toolbox for the industrial IoT.
+It comes with a rich graphical user interface targeted at non-technical users and provides the following features:
-Pipeline elements in StreamPipes can be installed at runtime - the built-in SDK allows to easily implement new
-pipeline elements according to your needs. Pipeline elements are standalone microservices that can run anywhere -
-centrally on your server, in a large-scale cluster or close at the edge.
+* Quickly connect >20 industrial data sources and protocols such as OPC-UA, PLCs, MQTT, REST, Kafka and others
+* Create data harmonization and analytics pipelines using > 100 algorithms and many data sinks to forward data to third-party systems
+* Use the data explorer to visually explore historical data with many widgets tailored for time-series data.
+* A live dashboard to display real-time data from data sources and pipelines, e.g., for shopfloor monitoring.
-## Use Cases
+StreamPipes is highly extensible and includes a Java and Python (currently in development phase) SDK to create new
+pipeline elements and adapters.
+Pipeline elements are standalone microservices that can run anywhere -
+centrally on your server or close at the edge.
+You want to employ your own machine learning model on live data?
+Just write your own data processor and make it reusable as a pipeline element.
-StreamPipes allows you to connect IoT data sources using the SDK or the built-in graphical tool **StreamPipes
-Connect**.
+Besides that, StreamPipes includes features for production deployments:
+* Assign resources such as pipelines, data streams and dashboards to assets for better organization
+* Built-in user and access rights management
+* User self-registration and email support
+* Export and import resources
-The extensible toolbox of data processors and sinks supports use cases such as
-* Continuously **store** IoT data streams to third party systems (e.g., databases)
-* **Filter** measurements on streams (e.g., based on thresholds or value ranges)
-* **Harmonize** data by using data processors for transformations (e.g., by converting measurement units and data types
- or by aggregating measurements)
-* **Detect situations** that should be avoided (e.g., patterns based on time windows)
-* Wrap **Machine Learning models** into data processors to perform classifications or predictions on sensor and image data
-* **Visualize** real-time data from sensors and machines using the built-in Live Dashboard
+## User interface
+
+* Connect data from an OPC-UA server:
+
+
+
+* Create a pipeline to detect a trend:
+
+
+
+* Visually analyze data using the data explorer:
+
+
## Installation
@@ -98,6 +110,12 @@ Please follow the instructions provided in the corresponding `README.md` to get
For a more in-depth manual, read the [installation guide](https://streampipes.apache.org/docs/docs/try-installation.html).
+> TL;DR: Download the latest release, switch to the ``installer/compose`` directory and run ``docker-compose up -d``.
+
+## Documentation
+
+The full documentation, including an overview of pipeline elements, a developer guide and several tutorials is available at [https://streampipes.apache.org/docs/docs/user-guide-introduction.html](https://streampipes.apache.org/docs/docs/user-guide-introduction.html)
+
## Building StreamPipes
To properly build the StreamPipes core, the following tools should be installed:
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