Singer
Apache Camel
logstash
Apache Kafka
Airbyte
Talend Open Studio
Scriptella
Kettle Pentaho
Jupyter
Looker
Google BigQuery
Databricks
Presto DB
Rakam
Informatica
Concurrent
JupyterBased on our record, Jupyter seems to be a lot more popular than Singer. While we know about 206 links to Jupyter, we've tracked only 7 mentions of Singer. 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.
Coincidently, I saw a presentation today on a nice half-way-house solution: using embeddable Python libraries like Sling and dlt - both open-source. See https://www.youtube.com/watch?v=gAqOLgG2iYY There is also singer.io which is more of a protocol than a library, but can also be installed although it looks like it is a true community effort and not so well maintained. Source: 6 months ago
Singer is an open-source framework for data ingestion, which provides a standardized way to move data between various data sources and destinations (such as databases, APIs, and data warehouses). Singer offers a modular approach to data extraction and loading by leveraging two main components: Taps (data extractors) and Targets (data loaders). This design makes it an attractive option for data ingestion for... - Source: dev.to / about 1 year ago
Or you could build your own such system and run it on Airflow, Prefect, Dagster, etc. Check out the Singer project for a suite of Python packages designed for such a task. Quality varies greatly, though. Source: over 1 year ago
This is good advice and I think Airbyte created a great product here. I tried singer.io and pipewise but Airbyte is much better in my opinion and I love the UI. Source: almost 3 years ago
Suspect my question should have been regarding FREE systems, rather than BUYING a system. Sounds like singer.io will do what I need. Source: about 3 years ago
Interesting, I would have guessed you had used something jupyter-like: https://jupyter.org/ https://explorabl.es/all/. - Source: Hacker News / about 1 month ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / about 2 months ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 2 months ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / about 2 months ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 4 months ago
Apache Camel - Apache Camel is a versatile open-source integration framework based on known enterprise integration patterns.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
logstash - logstash is a tool for managing events and logs.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?