versatile-data-kit
pinot
versatile-data-kit | pinot | |
---|---|---|
52 | 15 | |
412 | 5,167 | |
1.5% | 1.4% | |
9.7 | 9.9 | |
7 days ago | 2 days ago | |
Python | Java | |
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.
versatile-data-kit
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Looking for a data blogger
Here's the project: https://github.com/vmware/versatile-data-kit
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Need advice on ETL tool
I don't really know if this would work for you because the UI is not functional yet, but a very simple REST API ingestion example here, there's one for csv too https://github.com/vmware/versatile-data-kit/wiki/Ingesting-data-from-REST-API-into-Database I can't imagine a simpler way unless it's really drag and drop.
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If dbt is the "T" part of an "ELT", what do you use for "EL"?
I work at VMware and we use one tool for the whole ELT, it was made internally as there was no good alternative at the time and now we opensourced it, here it is: https://github.com/vmware/versatile-data-kit
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Best way to fix errors in my data?
With my team we created csv ingestion plugin described here, maybe you want to try it out: https://github.com/vmware/versatile-data-kit/wiki/Ingesting-local-CSV-file-into-Database
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What Orchestration Tool do you use for batch ETL/ELT?
We use Versatile Data Kit for batch data job orchestration (https://github.com/vmware/versatile-data-kit)
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Dear, pipeline builders! Which step in your role is the most time consuming?
"suggestions on how to reduce the time spent on initially generating and adjusting the code" is using some tools that automate ELT. Here's one open-source tool I'm working on with my team: https://github.com/vmware/versatile-data-kit
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Problem definition / vibe check for a repo
here's the repo: https://github.com/vmware/versatile-data-kit
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Can we take a moment to appreciate how much of dataengineering is open source?
If you wish to contribute, projects usually have good first issues: https://github.com/vmware/versatile-data-kit/labels/good%20first%20issue If you wish to learn, check out examples: https://github.com/vmware/versatile-data-kit/tree/main/examples
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ETL question (noob)
Have you heard about versatile data kit (https://github.com/vmware/versatile-data-kit)? I think it meets your needs perfectly:
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DE Open Source
Versatile Data Kit is a framework to bBuild, run and manage your data pipelines with Python or SQL on any cloud https://github.com/vmware/versatile-data-kit here's a list of good first issues: https://github.com/vmware/versatile-data-kit/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22 Join our slack channel to connect with our team: https://cloud-native.slack.com/archives/C033PSLKCPR
pinot
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How to choose the right type of database
Apache Pinot: Tailored for providing ultra-low latency analytics at scale. Apache Pinot is widely used for real-time analytical solutions where rapid data insights and decision-making are critical.
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.
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🦿🛴Smarcity garbage reporting automation w/ ollama
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system
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Apache Pinot 1.0
There is indeed Spark support for writing new data into Pinot (https://docs.pinot.apache.org/basics/data-import/batch-inges...) as well as to query it (https://github.com/apache/pinot/blob/master/pinot-connectors...).
This does not run inside the Pinot cluster - you can use standard Spark execution engine to run this ingestion. In addition, Pinot also supports an out of the box ingestion capability from batch sources using the Minion framework (https://docs.pinot.apache.org/basics/components/cluster/mini...) that does not need any external component (like Spark)
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Ask HN: Who is hiring? (June 2023)
StarTree | Onsite | Mountain View CA, Bangalore India | Site Lead, SRE, Software Engineers (Backend, Data Infrastructure, Platform), Staff Security Engineer Compliance and Governance
You can find all the job postings here: https://startree.ai/careers
My name is Peter Corless and I am the Director of Product Marketing at StarTree (https://startree.ai/). We are a Mountain View, California based company and aer now opening an engineering operation in Bangalore, India.
We make StarTree Cloud, an Online Analytical Processing (OLAP) database-as-a-service (DBaaS) for real-time, user-facing analytics, powered by Apache Pinot.
Apache Pinot (https://pinot.apache.org/) is a top-level Apache Software Foundation (ASF) project that came out of LinkedIn. A lot of the PMCs for the Apache Pinot project work at StarTree. It is also used at Uber, Stripe, DoorDash, Just Eat Takeaway (GrubHub), and a lot of other organizations.
Apache Pinot is known for its ability to provide high concurrency — hundreds of thousands of QPS — against petabytes of data. It uses the star-tree index to provide really fast responses measured in milliseconds.
We're past 100 employees and looking for people who want to help grow us to the next orders of magnitude.
Let me know if you have questions or interest.
- Seeking Feedback on Siddhi
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When you should use columnar databases and not Postgres, MySQL, or MongoDB
But then you realize there are other databases out there focused specifically on analytical use cases with lots of data and complex queries. Newcomers like ClickHouse, Pinot, and Druid (all open source) respond to a new class of problem: The need to develop applications using endpoints published on analytical queries that were previously confined only to the data warehouse and BI tools.
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Building Apache Pinot and Presto
Recently, we have been surveying some streaming database solutions and the primary target is Apache Pinot, which fits our needs from the description and is therefore the primary target.
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Reducing Database Loading
There are many mainstream streaming databases, and Apache Pinot is the most popular one recently.
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How-to-Guide: Contributing to Open Source
Apache Pinot
What are some alternatives?
data-engineering-zoomcamp - Free Data Engineering course!
hudi - Upserts, Deletes And Incremental Processing on Big Data.
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
Trino - Official repository of Trino, the distributed SQL query engine for big data, former
quadratic - Quadratic | Data Science Spreadsheet with Python & SQL
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
pyramid-jsonapi - Auto-build JSON API from sqlalchemy models using the pyramid framework
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
dbt-data-reliability - dbt package that is part of 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.
kafka-observability - An exploration of observability for Kafka client applications
hamilton - A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system