jitsu
lightdash
Our great sponsors
jitsu | lightdash | |
---|---|---|
13 | 13 | |
3,845 | 3,399 | |
1.7% | 5.0% | |
9.8 | 10.0 | |
about 11 hours ago | about 6 hours ago | |
TypeScript | TypeScript | |
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.
jitsu
- Jitsu
- Any examples of working activist, socialist, or community-organizing software?
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Lesser Known Features of ClickHouse
you may check: https://github.com/jitsucom/jitsu. "Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days"
You can create an API endpoint, and send those JSON to it. In the "destination" part, it can sync to clickhouse (one of many choices, like redshift, snowflake,besides clickhouse) very quickly, and flatten the JSON into columns. If there is new key found in JSON, it will create a new column in clickhouse.
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Reference Data Stack for Data-Driven Startups
We also have telemetry set up on our Monosi product which is collected through Snowplow,. As with Airbyte, we chose Snowplow because of its open source offering and because of their scalable event ingestion framework. There are other open source options to consider including Jitsu and RudderStack or closed source options like Segment. Since we started building our product with just a CLI offering, we didn’t need a full CDP solution so we chose Snowplow.
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Data pipeline suggestions
Ingestion / Extraction: Airbyte, Singer, Jitsu
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Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
- Ask HN: Good open source alternatives to Google Analytics?
- Jitsu is a FOSS data integration platform that gathers events from several data sources (alternative to Segment)
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Launch HN: Jitsu (YC S20) – Open-Source Segment Alternative
I’m just saying this is better:
We are building Jitsu, (https://github.com/jitsucom/jitsu, https://jitsu.com/) We help companies collect events from their apps, websites, and APIs and send them to databases.
Think of us as an open-source Segment alternative.
lightdash
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Apache Superset
> YAML, pivoting being done in the frontend, no symmetric aggregates
(one of the maintainers of Lightdash) You touched on some of our most interesting problems here! Would be especially interested to hear about what you liked / didn't like about symmetric aggregates in Looker and how you find dev with YAML. If you have an idea of how you'd like these to look in Lightdash, the team would be really open to making that a reality.
For pivoting in the backend, this is coming! Issue here: https://github.com/lightdash/lightdash/issues/2907
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What are the 5 hottest dbt Repositories one should star on GitHub 2022?
What are the 5 hottest dbt Repositories one should star on Github 2022?
dbt is a software framework that sits in the middle of the ELT process. It represents the transformative layer after loading data from an original source. Dbt combines SQL with software engineering principles.
Here are my top5!
- Lightdash (https://github.com/lightdash/lightdash): Lightdash converts dbt models and makes it possible to define and easily visualize additional metrics via a visual interface.
- ⏎ re_data (https://github.com/re-data/re-data): Re-Data is an abstraction layer that helps users monitor dbt projects and their underlying data. For example, you get alerts when a test failed or a data anomaly occurs in a dbt project.
- evidence (https://github.com/evidence-dev/evidence): Evidence is another tool for lightweight BI reporting. With Evidence, you can build simple reports in "medium style" using SQL queries and Markdown.
- Kuwala (https://github.com/kuwala-io/kuwala): With Kuwala, a BI analyst can intuitively build advanced data workflows using a drag-drop interface on top of the modern data stack without coding. Behind the Scenes, the dbt models are generated so that a more experienced engineer can customize the pipelines at any time.
- fal ai (https://github.com/fal-ai/fal): Fal helps to run Python scripts directly from the dbt project. For example, you can load dbt models directly into the Python context which helps to apply Data Science libraries like SKlearn and Prophet in the dbt models.
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What are the hottest dbt Repositories you should star on Github 2022? - Here are mine.
Lightdash ( https://github.com/lightdash/lightdash ) Lightdash converts dbt models and makes it possible to define and easily visualize additional metrics via a visual interface. The front end helps to understand and extend the underlying SQL queries. Lightdash also visualizes business metrics and makes them shareable with the data team. It is also possible to integrate all data into another visualization tool.
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What are your hottest dbt repositories in 2022 so far? Here are mine!
- ⚡️ Lightdash: Lightdash converts dbt models and makes it possible to define and easily visualize additional metrics via a visual interface.
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Data pipeline suggestions
Visualization / Analysis: Lightdash, Superset
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Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
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Launch HN: Metaplane (YC W20) – Datadog for Data
1) An integration with Metabase Cloud is on our roadmap for Q1! We'd love to integrate with Lightdash, but they don't have a public API just yet[1].
2) Several of our customers use us to alert on schema changes in Postgres, specifically so they can get ahead of application database changes that will end up in the warehouse, so you're definitely not alone! Here's a link on how to connect postgres: https://docs.metaplane.dev/docs/postgres
That's an excellent stack and one we kept front and center when building out Metaplane, so definitely let us know if you have any feedback or suggestions here!
[1]: https://github.com/lightdash/lightdash/issues/632
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what's your experience with Looker ?
I would recommend lightdash which is essentially an open source Looker clone https://github.com/lightdash/lightdash
- a full semantic model based on dbt, dimensions, joins and metrics
- An open source alternative to Looker built using dbt. Made for analysts
What are some alternatives?
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.
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
Snowplow - The enterprise-grade behavioral data engine (web, mobile, server-side, webhooks), running cloud-natively on AWS and GCP
superset - Apache Superset is a Data Visualization and Data Exploration Platform
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Rakam - 📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
posthog-ios - PostHog iOS SDK
trino_data_mesh - Proof of concept on how to gain insights with Trino across different databases from a distributed data mesh
sqlpad - Web-based SQL editor. Legacy project in maintenance mode.
elementary - The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
streamlit - Streamlit — A faster way to build and share data apps.