kuzu
peloton
kuzu | peloton | |
---|---|---|
11 | 3 | |
1,052 | 1,888 | |
9.7% | - | |
9.9 | 10.0 | |
5 days ago | about 5 years ago | |
C++ | 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.
kuzu
- Unum: Vector Search engine in a single file
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Building a New Database Management System in Academia
These two posts[2,3] explain where we are from and where we're going, if anyone is interested.
[1]: https://github.com/kuzudb/kuzu
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Graph Database Community
Hi u/kyleireddit, I want to encourage you to try out KuzuDB: https://github.com/kuzudb/kuzu, which we are actively developing. One of our goals is to help educate developers more on where graph dbmss can offer value, so if you join our Slack channel and ask questions about graph dbmss and my students and I can answer some of your questions.
- Kùzu: an in-process property graph database management system (GDBMS)
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Best free graph database for order of 500 million nodes
Then you can try Kùzu: https://github.com/kuzudb/kuzu. It should do quite well. We are new but actively developing the system and would love to help you when you are prototyping your application.
- KùzuDB – In-Memory Graph Database
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PageRank Algorithm for Graph Databases
Not sqlite, but kuzu ( https://github.com/kuzudb/kuzu ) is an interesting project in this space. Fairly new, but already quite impressive IMHO.
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CIDR 2023 Database Conference from Memgraph’s Perspective
I already mentioned Kùzu folks. They are doing an outstanding job of explaining what they do. Just follow their web 😀 They presented KùzuDB paper which brings interesting concepts to the graph query executions called factorization, S-Join and ASP-Join.
- Bullshit Graph Database Performance Benchmarks
- What Every Competent Graph DBMS Should Do
peloton
-
Building a New Database Management System in Academia
Proud to see my name (https://twitter.com/YingjunWu) mentioned in Andy's blog. I was Andy's visiting PhD at CMU and was the top 1 contributor to Peloton (https://github.com/cmu-db/peloton).
Today, building a database from scratch is extremely difficult, for several reasons:
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Rethinking Stream Processing and Streaming Databases
I was one of the main authors of a research project called Peloton (https://github.com/cmu-db/peloton) which was later rebranded to NoisePage (https://github.com/cmu-db/noisepage). The initial version of RisingWave actually borrowed a lot from Peloton (fun fact: that's also how DuckDB https://duckdb.org/ started!), but we decided to rewrite in Rust due to development cost and security (e.g., memory leakage) considerations (more info: https://www.risingwave-labs.com/blog/building-a-cloud-database-from-scratch-why-we-moved-from-cpp-to-rust/).
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But that would mean caring about the little peons
I'll give you an example from my own industry. At my company we talk to university researchers, and one of the more famous university database researcher came to us to learn about our performance testing, because it turned out that the database they were working on for several years as a research project was completely unusable as they just forgot to think about that aspect. They had to abandon the project because there was no single feature that contributed to the performance issues and fixing the system was harder than starting from scratch. Here's the last commit if you don't believe me.
What are some alternatives?
Memgraph - Open-source graph database, tuned for dynamic analytics environments. Easy to adopt, scale and own.
risingwave - SQL stream processing, analytics, and management. We decouple storage and compute to offer speedy bootstrapping, dynamic scaling, time-travel queries, and efficient joins.
SimSIMD - Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, and C, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and Arm NEON & SVE 📐
mutable - A Database System for Research and Fast Prototyping
ustore - Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️
NetworkX - Network Analysis in Python
Apache AGE - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL.
graphdb-testing - Benchmarking various graph databases, engines, datastructures, and data stores.
sqlite3-bfsvtab-ext - A virtual table extension for breadth-first search queries in Sqlite3
simple-graph - This is a simple graph database in SQLite, inspired by "SQLite as a document database"
uform - Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️