BohuTANG

7 ms·

31.
The Cost of the 1B Row Challenge with Snowflake and Databend(databend.com)
2 points by BohuTANG 3y ago|1 comments
32.
by BohuTANG 3y ago
With Snowflake and #Databendtackling the #1BRC: - How fast can we process? - What's the cost?
33.
by BohuTANG 3y ago
Interesting! However, it's important to note that S3 Select isn't ideal for handling large-scale data scans, as this can lead to exorbitant costs. In contrast, Databend( https://github.com/datafuselabs/databend
34.
Optimizing Data Warehouse QA with GPT-4 in Databend(databend.com)
1 points by BohuTANG 3y ago|0 comments
35.
by BohuTANG 3y ago
Yes, we need a unified API layer like OpenDAL: https://github.com/apache/incubator-opendal
36.
by BohuTANG 3y ago
For http(s) remote file, we can support glob pattern, for example: https://<thehfurl>/resolve/main/data/0000[00-55].parquet ' Databend supports this pattern: https://databend.rs/doc&
37.
by BohuTANG 3y ago
Cool, thanks for the insight. Analyzing HuggingFace datasets is now easier: https://twitter.com/DatabendLabs/status/1725361248509067434
38.
by BohuTANG 3y ago
Great, I'm using it now. If Lexeme is similar to Typora ( https://typora.io ), it could be fantastic and might even surpass Typora in terms of quality. On the other hand, if Typora already has these features, it's quite
39.
by BohuTANG 3y ago
Recommand Apache OpenDAL if you're using S3 to access your data. It's a unified data access layer that simplifies pulling data across different storage backends. https://github.com/apache/incubator-opendal
40.
by BohuTANG 3y ago
We(Databend Labs) benchmarked #TPCH-SF100 on S3, Wasabi, Backblaze B2, and Cloudflare R2: #S3 leads with its direct connect feature. #Wasabi offers good performance. #B2 and #R2 may not be suitable for big data needs Details: https:&#x2
41.
Revealed: Which Object Storages Are Best for Big Data Analytics?(twitter.com)
1 points by BohuTANG 3y ago|1 comments
42.
by BohuTANG 3y ago
DatabendLabs benchmarked TPCH-SF100 on Amazon S3, Wasabi, Backblaze B2, and Cloudflare R2.
43.
by BohuTANG 3y ago
Indeed, under a pay-as-you-go model, if there's a lack of precise control over the warehouse, such as a 10-minute suspension, it could lead to significant waste. This is because most queries might only take a few seconds, and the rest
44.
Databend and the rise of Data warehouse as a code(datamonkeysite.com)
1 points by BohuTANG 3y ago|0 comments
45.
by BohuTANG 4y ago
Good job! Databend has a AI_TO_SQL function to do it: https://databend.rs/doc/sql-functions/ai-functions/ai-to-sql
46.
by BohuTANG 5y ago
Well. 1. With the improvement of the rust ecosystem, using rust has made database development faster and easy, for example datafuse use the tokio to implement the pipeline https://github.com/datafuselabs/datafuse/t
47.
by BohuTANG 5y ago
Sure, datafuse is still working in progress. TPCH (mainly for JOIN) will be fully supported in Beta version. Datafuse team are mainly working on the Alpha version.
48.
by BohuTANG 5y ago
Datafuse team mainly from the ClickHouse community, but more focused on the cloud database. Datafuse Labs team: https://github.com/orgs/datafuselabs/people
49.
by BohuTANG 15y ago
Hello, The different than the more than 100 other NoSQL databases are: nessDB is very fast, on-disk storage engine,it's using LSM-Tree, which has a very better performance than B+Trees.There are a performance comparison test with tcbdb,Mong
50.
by BohuTANG 15y ago
And supports Redis-Protocol(PING,SET,MSET,GET,MGET,DEL,EXISTS,INFO,SHUTDOWN).
51.
nessDB:a very fast key/value storage engine 1.8-rc1 released(groups.google.com)
5 points by BohuTANG 15y ago|3 comments
52.
NessDB:a fast Key/Value Database Storage Engine
7 points by BohuTANG 15y ago|3 comments