dagster
nodejs-bigquery
dagster | nodejs-bigquery | |
---|---|---|
46 | 43 | |
10,274 | 457 | |
2.7% | 0.9% | |
10.0 | 8.0 | |
4 days ago | 4 days ago | |
Python | TypeScript | |
Apache License 2.0 | Apache License 2.0 |
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.
dagster
- Experience with Dagster.io?
-
Dagster tutorials
My recommendation is to continue on with the tutorial, then look at one of the larger example projects especially the ones named “project_”, and you should understand most of it. Of what you don't understand and you're curious about, look into the relevant concept page for the functions in the docs.
-
The Dagster Master Plan
I found this example that helped me - https://github.com/dagster-io/dagster/tree/master/examples/project_fully_featured/project_fully_featured
-
What are some open-source ML pipeline managers that are easy to use?
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home
-
The Why and How of Dagster User Code Deployment Automation
In Helm terms: there are 2 charts, namely the system: dagster/dagster (values.yaml), and the user code: dagster/dagster-user-deployments (values.yaml). Note that you have to set dagster-user-deployments.enabled: true in the dagster/dagster values-yaml to enable this.
-
Best Orchestration Tool to run dbt projects?
Dagster seemed really cool when I looked into it as an alternative to airflow. I especially like the software defined assets and built-in lineage which I haven't seen in any other tool. However it seems it does not support RBAC which is a pretty big issue if you want a self-service type of architecture, see https://github.com/dagster-io/dagster/issues/2219. It does seem like it's available in their hosted version, but I wanted to run it myself on k8s.
-
dbt Cloud Alternatives?
Dagster? https://dagster.io
-
What's the best thing/library you learned this year ?
One that I haven't seen on here yet: dagster
- Anyone have an example of a project where a handful of the more popular Python tools are used? (E.g. airbyte, airflow, dbt, and pandas)
- Can we take a moment to appreciate how much of dataengineering is open source?
nodejs-bigquery
-
Wrangling BigQuery at Reddit
If you've ever wondered what it's like to manage a BigQuery instance at Reddit scale, know that it's exactly like smaller systems just with much, much bigger numbers in the logs. Database management fundamentals are eerily similar regardless of scale or platform; BigQuery handles just about anything we throw at it, and we do indeed throw it the whole book. Our BigQuery platform is more than 100 petabytes of data that supports data science, machine learning, and analytics workloads that drive experiments, analytics, advertising, revenue, safety, and more. As Reddit grew, so did the workload velocity and complexity within BigQuery and thus the need for more elegant and fine-tuned workload management.
-
Building a dev.to analytics dashboard using OpenSearch
Now I know I've got some data I could use, I now need to find a platform that I can use to analyse the data coming from the Forem API. I did consider some other pieces of software, such as Google BigQuery (with looker studio) and ElasticSearch (with Kibana), I ultimately went with OpenSearch which is essentially a forked version of ElasticSearch maintained by AWS. The main reasons are that I could host it locally for free (unlike BigQuery). I do have some prior experience with both elastic (back when it was called ELK) and OpenSearch, but my work with OpenSearch was far more recent, so I decided to go with that.
- Como evitar SQL Injection utilizando client do BigQuery
- Learning Excel. Is there a resource for fake data sets like retail and wholesale inventories and sales histories etc for testing and practice?
-
How to Totally Fubar Your Cloud Infrastructure Costs
First, in one of our recent projects, we helped our client to run the cloud-based infrastructure of their entirely automated, real-time SEO platform. The solution rested in the safe familiarity of Google’s popular cloud-based data centres (i.e. Google Cloud Platform), whilst also making use of BigQuery — a serverless, multi-cloud data warehouse.
-
Data Analytics at Potloc I: Making data integrity your priority with Elementary & Meltano
Bigquery as our data warehouse
-
I've tried really hard but need some help please. Bigquery not returning data after 2019.
This post in github thinks it may be an error in bigquery's backend.
-
Deploying a Data Warehouse with Pulumi and Amazon Redshift
A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of data-warehouse products include Snowflake, Google BigQuery, Azure Synapse Analytics, and Amazon Redshift — all of which, incidentally, are easily managed with Pulumi.
- [Question] Which GCP tool should I use to build a Business decisional dashboard?
-
Designing a Video Streaming Platform 📹
Google BigQuery
What are some alternatives?
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
MLflow - Open source platform for the machine learning lifecycle
streamlit - Streamlit — A faster way to build and share data apps.
meltano
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications