greptimedb
Numba
greptimedb | Numba | |
---|---|---|
16 | 124 | |
3,781 | 9,452 | |
4.8% | 1.1% | |
9.9 | 9.9 | |
about 20 hours ago | 6 days ago | |
Rust | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" 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.
greptimedb
- GreptimeDB: A fast and cost-effective alternative to InfluxDB
- Another distributed time-series database written in Rust
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GreptimeAI + Xinference - Efficient Deployment and Monitoring of Your LLM Applications
GreptimeAI, built upon the open-source time-series database GreptimeDB, offers an observability solution for Large Language Model (LLM) applications, currently supporting both LangChain and OpenAI's ecosystem. GreptimeAI enables you to understand cost, performance, traffic and security aspects in real-time, helping teams enhance the reliability of LLM applications.
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What's everyone working on this week (49/2023)?
Continuing to work hard on a new MetricEngine in GreptimeDB. BTW, If you have a keen interest in Rust or database development, GreptimeDB might be a good starting point. Check it out for some good first issues here.
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Practical Tips for Refactoring Release CI using GitHub Actions
Since the very first day of GreptimeDB going open-source, it embraced the automated software building process with GitHub Actions, and leading to the inaugural Release Pipeline.
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GreptimeCloud - A Fully Managed Serverless Prometheus Backend
Born from the open-source project GreptimeDB, GreptimeCloud serves as a fully-managed, serverless cloud backend for Prometheus, offering integrated support for remote read/write protocols and PromQL as one of our primary query languages.
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Bridging Async and Sync Rust Code - A lesson learned while working with Tokio
Recently, while working on our GreptimeDB project, we encountered an issue with calling asynchronous Rust code in a synchronous context.
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A Deep Dive into PromQL — Promql Parser v0.1.0 Written in Rust is Now Available
To explore data stored in GreptimeDB through PromQL, GreptimeDB needs to provide the ability to parse the query into AST (abstract syntax tree), and retrieve data from memory or disk via logical and physical plans. Since there is no ready-to-use PromQL Rust Parser, our team decides to develop it by ourselves. We’re glad to announce that promql-parser v0.1.0 is now available.
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Extending Python with Rust
This is truly a fantastic combination -- implement the logic in Rust and use it in Python. GreptimeDB also implements a similar functionality that allows writing Python script to do post-process of SQL query results, with the help of RustPython and Arrow. Maybe this combination can bring a sweet point between performance and efficiency.
docs: https://docs.greptime.com/user-guide/coprocessor-and-scripti...
code: https://github.com/GreptimeTeam/greptimedb/tree/develop/src/...
Numba
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Mojo🔥: Head -to-Head with Python and Numba
Around the same time, I discovered Numba and was fascinated by how easily it could bring huge performance improvements to Python code.
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Is anyone using PyPy for real work?
Simulations are, at least in my experience, numba’s [0] wheelhouse.
[0]: https://numba.pydata.org/
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Any data folks coding C++ and Java? If so, why did you leave Python?
That's very cool. Numba introduces just-in-time compilation to Python via decorators and its sole reason for being is to turn everything it can into abstract syntax trees.
- Using Matplotlib with Numba to accelerate code
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Python Algotrading with Machine Learning
A super-fast backtesting engine built in NumPy and accelerated with Numba.
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PYTHON vs OCTAVE for Matlab alternative
Regarding speed, I don't agree this is a good argument against Python. For example, it seems no one here has yet mentioned numba, a Python JIT compiler. With a simple decorator you can compile a function to machine code with speeds on par with C. Numba also allows you to easily write cuda kernels for GPU computation. I've never had to drop down to writing C or C++ to write fast and performant Python code that does computationally demanding tasks thanks to numba.
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Codon: Python Compiler
Just for reference,
* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."
* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.
* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."
* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."
* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"
[0] https://github.com/Nuitka/Nuitka
[1] https://www.pypy.org/
[2] https://cython.org/
[3] https://numba.pydata.org/
[4] https://github.com/pyston/pyston
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This new programming language has the potential to make python (the dominant language for AI) run 35,000X faster.
For the benefit of future readers: https://numba.pydata.org/
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Two-tier programming language
Taichi (similar to numba) is a python library that allows you to write high speed code within python. So your program consists of slow python that gets interpreted regularly, and fast python (fully type annotated and restricted to a subset of the language) that gets parallellized and jitted for CPU or GPU. And you can mix the two within the same source file.
- Numba Supports Python 3.11
What are some alternatives?
risingwave - Cloud-native SQL stream processing, analytics, and management. KsqlDB and Apache Flink alternative. 🚀 10x more productive. 🚀 10x more cost-efficient.
NetworkX - Network Analysis in Python
cnosdb - A cloud-native open source distributed time series database with high performance, high compression ratio and high availability. http://www.cnosdb.cloud
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
FlashDB - An ultra-lightweight database that supports key-value and time series data | 一款支持 KV 数据和时序数据的超轻量级数据库
Dask - Parallel computing with task scheduling
datafuse - An elastic and reliable Cloud Warehouse, offers Blazing Fast Query and combines Elasticity, Simplicity, Low cost of the Cloud, built to make the Data Cloud easy [Moved to: https://github.com/datafuselabs/databend]
cupy - NumPy & SciPy for GPU
numexpr - Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
corrosion - Gossip-based service discovery (and more) for large distributed systems.
SymPy - A computer algebra system written in pure Python