awesome-modern-cpp
materialize
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awesome-modern-cpp | materialize | |
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15 | 117 | |
11,315 | 5,567 | |
- | 1.0% | |
3.5 | 10.0 | |
3 months ago | 4 days ago | |
HTML | Rust | |
- | GNU General Public License v3.0 or later |
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.
awesome-modern-cpp
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Ask HN: What are great resources to catch up C++?
seriously, don't bother with c++. it will become irrelevant eventually.
but if you choose to ignore my advice, check[0] these[1]
[0]: https://github.com/AnthonyCalandra/modern-cpp-features
[1]: https://github.com/rigtorp/awesome-modern-cpp
- Melyek a "legjobb" programozási nyelvek karrier és lehetőségek szempontjából 2023-ban?
- Ask HN: Who is using C++ as the main language for new project?
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Tips for starting with c++ after python
I can't recommend a course in c++, but check out Awesome Modern C++
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Anything similar to the Odin project but for learning C++?
1) Some collections of interesting stuff are sometimes under "awesomexyz" on github. ( the one I included here probably isn't the _best for someone new to C++ but I'm including it anyway) * https://github.com/rigtorp/awesome-modern-cpp
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Random Weekly Discussion - December 31, 2021
https://awesomecpp.com/ compiled list of c++ resources, only be aware of these no need to crunch through all
- Best books and courses to learn C++?
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How does a real world look like?
If you want more repositories and references, check out this link: awesome-modern-cpp
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I know Python basics, what next?
This might help: https://github.com/rigtorp/awesome-modern-cpp/blob/master/README.md
- A guide to learn C++ by my own.
materialize
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Ask HN: How Can I Make My Front End React to Database Changes in Real-Time?
[2] https://materialize.com/
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
To fully leverage the data is the new oil concept, companies require a special database designed to manage vast amounts of data instantly. This need has led to different database forms, including NoSQL databases, vector databases, time-series databases, graph databases, in-memory databases, and in-memory data grids. Recent years have seen the rise of cloud-based streaming databases such as RisingWave, Materialize, DeltaStream, and TimePlus. While they each have distinct commercial and technical approaches, their overarching goal remains consistent: to offer users cloud-based streaming database services.
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Proton, a fast and lightweight alternative to Apache Flink
> Materialize no longer provide the latest code as an open-source software that you can download and try. It turned from a single binary design to cloud-only micro-service
Materialize CTO here. Just wanted to clarify that Materialize has always been source available, not OSS. Since our initial release in 2020, we've been licensed under the Business Source License (BSL), like MariaDB and CockroachDB. Under the BSL, each release does eventually transition to Apache 2.0, four years after its initial release.
Our core codebase is absolutely still publicly available on GitHub [0], and our developer guide for building and running Materialize on your own machine is still public [1].
It is true that we substantially rearchitected Materialize in 2022 to be more "cloud-native". Our new cloud offering offers horizontal scalability and fault tolerance—our two most requested features in the single-binary days. I wouldn't call the new architecture a microservices design though! There are only 2-3 services, each quite substantial, in the new architecture (loosely: a compute service, an orchestration service, and, soon, a load balancing service).
We do push folks to sign up for a free trial of our hosted cloud offering [2] these days, rather than trying to start off by running things locally, as we generally want folks' first impression of Materialize to be of the version that we support for production use cases. A all-in-one single machine Docker image does still exist, if you know where to look, but it's very much use-at-your-own-risk, and we don't recommend using it for anything serious, but it's there to support e.g. academic work that wants to evaluate Materialize's capabilities to incrementally maintain recursive SQL queries.
If folks have questions about Materialize, we've got a lively community Slack [3] where you can connect directly with our product and engineering teams.
[0]: https://github.com/MaterializeInc/materialize/tree/main
- What I Talk About When I Talk About Query Optimizer (Part 1): IR Design
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We Built a Streaming SQL Engine
Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views.
https://github.com/timelydataflow/differential-dataflow
https://materialize.com/
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Ask HN: Who is hiring? (October 2023)
Materialize | Full-Time | NYC Office or Remote | https://materialize.com
Materialize is an Operational Data Warehouse: A cloud data warehouse with streaming internals, built for work that needs action on what’s happening right now. Keep the familiar SQL, keep the proven architecture of cloud warehouses but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date.
Materialize is the operational data warehouse built from the ground up to meet the needs of modern data products: Fresh, Correct, Scalable — all in a familiar SQL UI.
Senior/Staff Product Manager - https://grnh.se/69754ebf4us
Senior Frontend Engineer - https://grnh.se/7010bdb64us
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Investors include Redpoint, Lightspeed and Kleiner Perkins.
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Ask HN: Who is hiring? (June 2023)
Materialize | EM (Compute), Senior PM | New York, New York | https://materialize.com/
You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date.
That is Materialize, the only true SQL streaming database built from the ground up to meet the needs of modern data products: Fresh, Correct, Scalable — all in a familiar SQL UI.
Engineering Manager, Compute - https://grnh.se/4e14099f4us
Senior Product Manager - https://grnh.se/587c36804us
VP of Marketing - https://grnh.se/9caac4b04us
- What are your favorite tools or components in the Kafka ecosystem?
- Ask HN: Who is hiring? (May 2023)
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Dozer: A scalable Real-Time Data APIs backend written in Rust
How does it compare to https://materialize.com/ ?
What are some alternatives?
immer - Postmodern immutable and persistent data structures for C++ — value semantics at scale
ClickHouse - ClickHouse® is a free analytics DBMS for big data
thonny - Python IDE for beginners
risingwave - Cloud-native SQL stream processing, analytics, and management. KsqlDB and Apache Flink alternative. 🚀 10x more productive. 🚀 10x more cost-efficient.
notepad-plus-plus - Notepad++ official repository
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
windmap
rust-kafka-101 - Getting started with Rust and Kafka
py-must-watch - Must-watch videos about Python
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
pythonds - Problem Solving with Algorithms and Data Structures using Python
scryer-prolog - A modern Prolog implementation written mostly in Rust.