rudderstack-docs
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rudderstack-docs | ClickHouse | |
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20 | 208 | |
20 | 34,054 | |
- | 2.3% | |
3.5 | 10.0 | |
17 days ago | 1 day ago | |
JavaScript | C++ | |
MIT License | 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.
rudderstack-docs
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MDS Newsletter #12
2/ Featured tools this week - Transform and RudderStack
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How To Event Stream From Your Gatsby Website Using Open Source RudderStack
RudderStack is an open-source Customer Data Pipeline that allows you to track and send real-time events from your web, mobile, and server-side sources to your entire customer data stack. Our primary repository - rudder-server - is open-sourced on GitHub.
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Customer Data Pipelines Play a Key Role in Data Privacy
This post will explain how your customer data pipeline can help improve your data privacy and how to ensure your data privacy with RudderStack.
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Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
However, limitations to traditional CDPs, especially around connecting to best-of-breed customer tooling and exposing data for use across an organization have driven a new generation of non-CDPs. Solutions like Snowplow's (website, GitHub) data delivery platform and RudderStack's (website, GitHub) customer data platform for developers ingest data from a multitude of sources, apply in-stream transformations, and route data to your data warehouse, like Snowplow, or your warehouse plus your preferred customer tooling destinations for activation, like RudderStack.
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RudderStack + Blendo: Better Together
I learned many lessons from this journey - lessons that deserve a post of their own - but there's one lesson that I learned early on that stands out. In this blog, I talk about why we merged Blendo with RudderStack, building the team and working together to build a great product.
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The Open Source Story - Open Sourcing RudderStack Blog and Docs
In fact, developers have already started contributing to our documentation. Recently, Benedikt from the Userlist team created the docs for the Userlist destination for RudderStack (see the pull request here). They also built the Userlist integration, submitted a pull request, and it is now live on our platform! This is the beauty of open source!
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How to plan and implement a customer data tracking strategy for your Micro-SaaS
TLDR: general steps/starting point for setting up an app with Rudderstack ( or Segment) to track customer events
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Developing a Custom Plugin using Flutter
As a part of our SDK roadmap at RudderStack, we wanted to develop a Flutter SDK. Our existing SDKs include features such as storing event details and persisting user details on the database, and much more. However, these features are already implemented in our Android and iOS SDKs.
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Visualize Stripe Payments Data in Postgres using SQL
To load Stripe data into Postgres, you can use platforms such as Stitch Data and Rudderstack. In this guide, we will use Stitch Data because it is a cheap and a fast solution.
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Dogfooding at RudderStack: Tracking Plans Part 1
With your Tracking Plans in place, you can use the existing Data Governance API's to evaluate your inbound events, payload samples and metadata to compare them against your plans. You can also use the RudderTyper tool we're releasing alongside Tracking Plans. RudderTyper is a tool for generating strongly-typed RudderStack analytics library wrappers based on your published tracking plan specs, meaning your data will conform to your defined schema upon capture.
ClickHouse
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We Built a 19 PiB Logging Platform with ClickHouse and Saved Millions
Yes, we are working on it! :) Taking some of the learnings from current experimental JSON Object datatype, we are now working on what will become the production-ready implementation. Details here: https://github.com/ClickHouse/ClickHouse/issues/54864
Variant datatype is already available as experimental in 24.1, Dynamic datatype is WIP (PR almost ready), and JSON datatype is next up. Check out the latest comment on that issue with how the Dynamic datatype will work: https://github.com/ClickHouse/ClickHouse/issues/54864#issuec...
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Build time is a collective responsibility
In our repository, I've set up a few hard limits: each translation unit cannot spend more than a certain amount of memory for compilation and a certain amount of CPU time, and the compiled binary has to be not larger than a certain size.
When these limits are reached, the CI stops working, and we have to remove the bloat: https://github.com/ClickHouse/ClickHouse/issues/61121
Although these limits are too generous as of today: for example, the maximum CPU time to compile a translation unit is set to 1000 seconds, and the memory limit is 5 GB, which is ridiculously high.
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Fair Benchmarking Considered Difficult (2018) [pdf]
I have a project dedicated to this topic: https://github.com/ClickHouse/ClickBench
It is important to explain the limitations of a benchmark, provide a methodology, and make it reproducible. It also has to be simple enough, otherwise it will not be realistic to include a large number of participants.
I'm also collecting all database benchmarks I could find: https://github.com/ClickHouse/ClickHouse/issues/22398
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How to choose the right type of database
ClickHouse: A fast open-source column-oriented database management system. ClickHouse is designed for real-time analytics on large datasets and excels in high-speed data insertion and querying, making it ideal for real-time monitoring and reporting.
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Writing UDF for Clickhouse using Golang
Today we're going to create an UDF (User-defined Function) in Golang that can be run inside Clickhouse query, this function will parse uuid v1 and return timestamp of it since Clickhouse doesn't have this function for now. Inspired from the python version with TabSeparated delimiter (since it's easiest to parse), UDF in Clickhouse will read line by line (each row is each line, and each text separated with tab is each column/cell value):
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The 2024 Web Hosting Report
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules.
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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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Proton, a fast and lightweight alternative to Apache Flink
Proton is a lightweight streaming processing "add-on" for ClickHouse, and we are making these delta parts as standalone as possible. Meanwhile contributing back to the ClickHouse community can also help a lot.
Please check this PR from the proton team: https://github.com/ClickHouse/ClickHouse/pull/54870
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1 billion rows challenge in PostgreSQL and ClickHouse
curl https://clickhouse.com/ | sh
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We Executed a Critical Supply Chain Attack on PyTorch
But I continue to find garbage in some of our CI scripts.
Here is an example: https://github.com/ClickHouse/ClickHouse/pull/58794/files
The right way is to:
- always pin versions of all packages;
What are some alternatives?
pub-dev - The pub.dev website
loki - Like Prometheus, but for logs.
dbt-spark - dbt-spark contains all of the code enabling dbt to work with Apache Spark and Databricks
duckdb - DuckDB is an in-process SQL OLAP Database Management System
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]
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
nodejs-bigquery - Node.js client for Google Cloud BigQuery: A fast, economical and fully-managed enterprise data warehouse for large-scale data analytics.
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
BigQuery-Python - Simple Python client for interacting with Google BigQuery.
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
WordPress - WordPress, Git-ified. This repository is just a mirror of the WordPress subversion repository. Please do not send pull requests. Submit pull requests to https://github.com/WordPress/wordpress-develop and patches to https://core.trac.wordpress.org/ instead.
arrow-datafusion - Apache DataFusion SQL Query Engine