papermark
ClickHouse
papermark | ClickHouse | |
---|---|---|
26 | 211 | |
2,591 | 35,054 | |
- | 2.6% | |
9.9 | 10.0 | |
2 days ago | 2 days ago | |
TypeScript | C++ | |
GNU Affero General Public License v3.0 | 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.
papermark
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Show HN: Open-source alternative to pdf.ai, ask your pdf and other AI for docs
Simple AI assistant for documents made open source
Can be used for your docs or also for shared documents.
It is currently a part of Papermark, open source Docsend alternative for sharing docs quickly and getting analytics on each page.
Thinking on investing more time in it, and building more advanced work with many docs.
Any contributors are welcome here https://github.com/mfts/papermark
- Papermark: Open-Source DocSend Alternative
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Deploy a WebAssembly-powered Next.js app on Vercel serverless functions
Caveat: this serverless implementation only works with files smaller than 4MB. If you need to upload larger files, you'll want to use a client-side upload (see more on GitHub).
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🏞️5 beautiful open-source web apps to learn from and get inspired 🙇♀️💡
Papermark has recently been getting a lot of love from the community, especially for its clean design and intuitive interface. Although it might look simple from the outside, this app packs a lot of functionalities that make everything work smoothly: file upload, email sending, built-in analytics, and custom domains…
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Building an Email-Protected Notion Page Using Next.js and React-Notion-X
I would be grateful if you could give us a star! Don't forget to share your thoughts in the comments section ❤️ https://github.com/mfts/papermark
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Open Source alternatives to tools you Pay for
Papermark - Open Source Alternative to Docsend
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Launch: Share Notion Pages on Custom Domains with Real-Time Analytics
Check out the code and setup: https://github.com/mfts/papermark and how to get started: https://www.papermark.io/share-notion-page
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Show HN: Papermark – the open-source DocSend alternative with custom domains
Hi HN! We’re Marc and Iuliia from Papermark (https://papermark.io). We're building an open-source, modern document sharing platform with real-time engagement analytics and 100% customization.
It all started as a tweet [1] and led to our launch on Product Hunt [2] last month. We crossed over 1000 stars and over 10 contributors on GitHub (https://github.com/mfts/papermark).
Incumbents, like DocSend, founded in the early 2010s have been acquired already and just don't innovate anymore. Their main priority is enterprise clients.
As founders and developers ourselves we always felt that our needs are not being served. We struggle to get actionable insights when sending pitch decks to investors or sales proposals to customers. We are missing the flexibility and integrations with our existing applications and tech stack.
That’s why we are building Papermark.
Our bigger vision
A developer-friendly document sharing platform doesn’t exist yet! We believe that document analytics should be available to anyone that is creating and sharing documents.
- Rich observability: Don’t get left in the dark when sharing a document. Papermark will provide full transparency by exposing all document-related events through webhooks.
- Papermark – The Open-Source Docsend Alternative
- Build an Expandable / Collapsible Data Table with 2 shadcn/ui Components
ClickHouse
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Universal Data Migration: Using Slingdata to Transfer Data Between Databases
ClickHouse installed and running.
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Simplified API Creation and Management: ClickHouse to APISIX Integration Without Code
In the world of data management and web services, creating and managing APIs can often be a complex and time-consuming task. However, with the right tools, this process can be significantly simplified. In this article, we will explore how to create APIs for fetching data from ClickHouse tables without writing any code and manage these APIs using APISIX. ClickHouse, a fast and open-source columnar database management system, provides an HTTP interface by default, enabling easy access to data. By integrating this with APISIX, an open-source API gateway, we can not only manage and log our APIs but also leverage a host of features provided by APISIX to enhance our API management capabilities.
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The new APT 3.0 solver
I've made a library named "glibc-compatibility": https://github.com/ClickHouse/ClickHouse/tree/master/base/gl...
When linking with this library, the resulting binary will not depend on the new symbol versions. It will run on glibc 2.4 and on systems as old as Ubuntu 8.04 and CentOS 5 even when built on the most modern system.
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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.
What are some alternatives?
t3-turbo-and-clerk - A t3 Turbo starter with Clerk as the auth provider.
loki - Like Prometheus, but for logs.
nextjs-resume - A curriculum vitae inspired by read.cv, build with Next.js and Tailwind CSS
duckdb - DuckDB is an analytical in-process SQL database management system
twitterbio - Generate your Twitter bio with Mixtral and GPT-3.5.
Trino - Official repository of Trino, the distributed SQL query engine for big data, former
open-previews - Open source preview comments
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
twitter-algorithm - The official Twitter ranking algorithm
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
pkgx - the last thing you’ll install
datafusion - Apache DataFusion SQL Query Engine