HPKV is a new key-value store boasting faster performance than Redis, achieved through a novel lock-free B+ tree implementation. It's bi-directional, allowing efficient retrieval by both key and value, and offers persistence to disk. Designed for embedded and server-side use cases, HPKV supports multiple languages (C, C++, Python, Java, Go, and JavaScript) and provides various features like range scans, prefix scans, and TTL. It's available under the Apache 2.0 license, promoting open-source contribution and adoption.
The Hacker News post introduces hpkv (High-Performance Key-Value store), a novel key-value data store boasting superior performance compared to established solutions like Redis. Hpkv is designed as a bi-directional, persistent store, meaning data flows seamlessly in both directions (read and write) and is durably saved to prevent data loss upon system restart. The developers emphasize speed as a primary differentiator, claiming faster performance than Redis, a popular in-memory data store known for its speed. This performance gain is attributed to hpkv's architectural design, although the specifics are not detailed in the brief announcement.
Persistence is a crucial feature, ensuring data reliability and eliminating the need for complex data recovery mechanisms in case of failures. Hpkv manages this persistence internally, abstracting away the complexities of data durability from the user.
The project is open-source, inviting community contributions and scrutiny. The source code is available on GitHub, providing transparency and allowing developers to examine the implementation details. This openness fosters collaboration and potentially accelerates the project's development and refinement.
The announcement itself is concise, primarily focusing on the core features: bi-directionality, persistence, and speed. It serves as an initial introduction to hpkv, aiming to pique interest and encourage further exploration via the provided GitHub repository. While the post highlights the key advantages, it lacks extensive technical details regarding the underlying architecture, storage engine, and specific performance benchmarks to substantiate the performance claims. This suggests the project is likely in its early stages, with more comprehensive documentation and performance evaluations expected as it matures. The emphasis on being faster than Redis positions hpkv as a potential contender in the high-performance key-value store space, targeting applications requiring rapid data access and guaranteed data durability.
Summary of Comments ( 9 )
https://news.ycombinator.com/item?id=43387834
Hacker News users discussed the performance claims of hpkv, questioning the benchmark methodology and the choice of Redis as a comparison point. Several commenters pointed out that using
redis-benchmarkwith a pipeline size of 1 is unfair to Redis, significantly hindering its performance. Others suggested alternative benchmarking tools and emphasized the importance of real-world workload simulations. The lack of detail about hpkv's persistence mechanism and data safety guarantees also drew scrutiny. Some expressed interest in the project but desired more information about its architecture and use cases. A few users pointed out potential bugs in the benchmarking script itself, further questioning the validity of the presented results.The Hacker News post "Show HN: A bi-directional, persisted KV store that is faster than Redis" linking to hpkv.io generated a moderate number of comments, primarily focusing on technical aspects and comparisons to existing solutions.
Several commenters expressed skepticism regarding the performance claims, particularly the assertion of being "faster than Redis." They pointed out the need for more rigorous benchmarking and detailed methodology to substantiate such a claim. Specific concerns included the lack of clarity on the types of benchmarks run, the hardware used, and the specific Redis configuration being compared against. Some users requested benchmark results using established tools like
redis-benchmarkto provide a more standardized comparison.Discussion also arose around the choice of language (Rust) and its impact on performance. While some lauded Rust's speed and memory safety, others questioned whether these advantages alone could justify the performance claims, suggesting that algorithmic optimizations and data structures likely played a more significant role.
The project's novelty and potential use cases were also points of discussion. Some commenters saw value in the bi-directional nature of the key-value store, exploring potential applications in areas like graph databases and indexing. Others questioned the practical benefits of bi-directionality, suggesting that existing solutions with appropriate indexing could achieve similar functionality.
The persistence aspect of hpkv also drew some attention, with queries about the specific mechanisms employed for data persistence and the potential performance implications of these choices. Commenters also inquired about data durability guarantees and crash recovery capabilities.
A few commenters shared their own experiences with similar projects and offered alternative approaches to achieving high-performance key-value storage. They mentioned existing databases and libraries known for their speed and efficiency, suggesting that the author explore these for potential inspiration or comparison.
Overall, the comments reflect a cautious but curious reception to the project. While acknowledging the potential of hpkv, many commenters highlighted the need for more robust evidence to support the performance claims and a more in-depth explanation of the technical details. The discussion ultimately centered around the importance of thorough benchmarking, clear documentation, and careful consideration of existing solutions when introducing a new database technology.