killme2008

6 ms·

31.
Lessons from Mixing Rust and Java: Fast, Safe, and Practical(medium.com)
115 points by killme2008 1y ago|42 comments
32.
Deep dive into the challenges of building Kafka on top of S3(vutr.substack.com)
2 points by killme2008 1y ago|0 comments
33.
by killme2008 1y ago
Thanks for your feedback. We fixed the descriptions of log query endpoints. Hope it's more clear. Glad you're considering giving it a try and looking forward to your feedback.
34.
by killme2008 1y ago
Yes, so many startups are trying to solve the log issue in the current stack. In my personal observation, the vast majority of startups are still focused on the product layer and use ClickHouse directly for storage. However, ClickHouse’s ti
35.
by killme2008 1y ago
We'll find a way to fix it forever :D
36.
by killme2008 1y ago
In fact, we have an open-source query language, but it's still in experimental, so we don't present it on the website. The description of the enterprise feature is not precise. Sorry for the inconvenience. GreptimeDB also open-sou
37.
by killme2008 1y ago
Fair point. Joining time-series data with business data is often necessary. While GreptimeDB currently supports external tables for Parquet and CSV files, we plan to expand this support to include datasources like MySQL and PG in the future
38.
by killme2008 1y ago
The author is not a native speaker; I promised it's not an AI article but with some minor reviews from AI :)
39.
by killme2008 1y ago
I completely agree with you—Rust is not well-suited for application development. Application development requires rapid iteration, acceptable performance, and most importantly, a large developer community and a rich software ecosystem. Lang
40.
by killme2008 1y ago
Yes, GreptimeDB requires a time index column for optimized storage and querying. It's not a constraint of a primary key, but just an independent table constraint. Could you elaborate on why you find this inconvenient? I assumed logs, f
41.
by killme2008 1y ago
Thanks for pointing it out! The footer has been updated.
42.
by killme2008 1y ago
Agree. Leveraging capabilities provided by cloud vendors is always a good idea. However, as the scale grows, cost inevitably becomes an issue. Third-party solutions often offer cost advantages because they support multi-cloud deployments an
43.
by killme2008 1y ago
Thanks for your question. GreptimeDB, like MongoDB, is schemaless. When ingesting data via OTEL or its gRPC SDKs, it automatically creates tables by inferring the schema and dynamically adds new columns as needed. Secondly, I prefer wide ta
44.
by killme2008 1y ago
Interesting idea. Edge AI for initial anomaly detection before sending data to the central system makes sense. However, how do we handle global-level anomalies that require a broader perspective?
45.
by killme2008 1y ago
That's a good question. First of all, Kafka is still an event streaming platform and lacks database capabilities such as indexing and query optimization. Although ksql/Kafka Streams can perform computations based on consuming data
46.
by killme2008 1y ago
Yes, that's the LGTM(Loki, Grafana, Tempo, and Mimir) stack. First, the main issue with this stack is maintenance: managing multiple storage clusters increases complexity and resource consumption. Consolidating resources can improve ut
47.
by killme2008 1y ago
Agree. The new wide event pipeline should fully utilize cheaper storage options-object storage like S3. Includes both cold and hot data and maintains performance.
48.
by killme2008 1y ago
The extraction of raw data is the cooking or processing, and the results are ingested back into the same database. I think it's the approach described in this article.
49.
by killme2008 1y ago
This is something that has never happened before. When you need open source for promotion and fundraising, you embrace open source; when you want to make money, you kick open source to the curb. That's what we see.
50.
by killme2008 2y ago
Thank you for considering GreptimeDB! Feel free to give it a try next time, and we warmly welcome you to join our Slack community: https://greptime.com/slack
51.
by killme2008 2y ago
This architecture tries to address the key challenge with a disaggregated compute/storage architecture using object storage.
52.
by killme2008 2y ago
Delta Lake and Iceberg are great for managing offline, big data workloads like batch analytics and ETL on data lakes. They're not built for real-time queries or high-throughput writes. GreptimeDB, on the other hand, is optimized for re
53.
Open-source Rust database tops JSONBench using DataFusion(greptime.com)
13 points by killme2008 2y ago|5 comments
54.
by killme2008 2y ago
In the past, I also had doubts about whether a Rust database built on open-source components would be performance-limited, but this evaluation has dispelled our concerns. Apache DataFusion + Arrow + Parquet + OpenDAL, as a new data stack, h
55.
Rust database achieves top JSONBench ranking(greptime.com)
7 points by killme2008 2y ago|0 comments
56.
Show HN: GreptimeDB 2025 Roadmap(greptime.com)
7 points by killme2008 2y ago|0 comments
57.
From Pen and Paper to an AI Factory: McLaren's F1 Reinvention(mclaren.com)
8 points by killme2008 2y ago|3 comments
58.
by killme2008 2y ago
AI has accelerated McLaren's analysis and application of massive data, in deep collaboration with Dell Technologies. Through custom hardware and efficient algorithms, the team has significantly enhanced its real-time decision-making ca
59.
A Two-Year Journey Rebuilding an Algorithmic Trading Platform in Rust(nexustrade.io)
1 points by killme2008 2y ago|0 comments
60.
Reinforcement Learning: An Overview(arxiv.org)
6 points by killme2008 2y ago|1 comments

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