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vespa-engine
vespa
Java2017–2023
vespa-engine / vespa

vespa

The AI search platform

Data & DatabasesSystems & InfrastructureAI & Machine LearningLearning & ReferenceSearch & Information Retrieval
Explore on GitHubRead Hacker News discussions
15Distinct people
15Mentions
1Explicit recommenders
7.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The AI search platform

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

If ES doesn't work for you, I recommend Vespa. https://github.com/vespa-engine/vespa Others have made other suggestions, but Vespa has two unique features. First it is battle…

billythemaniam used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year15 dated mentions

Observed mentions: 2017-09-27 07:08:02 UTC to 2023-03-26 11:40:58 UTC.

02468102017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 10 mentions; 1 submissions, 9 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC1019
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC202
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101

What Hacker News says

15 sources
atombender·Nov 20, 2022
Vespa seems like a great match for Elastic's text and vector search, but not for classic "OLTP"-style queries. For example, until very recently Vespa did not even have case-sensitive string field matching [1]; doing a strict equality query on a string field was not possible, and the authors did not seem to see why it would be useful. Vespa lacks a lot of this kind of basic search functionality, making it less general-purpose than Elasticsearch. It's clear that it's a very powerful search engine, though it also feels antiquated in many ways. It's very obvious that it's an ancient project that has been worked on by many different people throughout the years, with no cohesive vision or design, though it does seem like they're slowly cleaning things up. (The documentation used to be much worse, for one.) [1] https://github.com/vespa-engine/ve
Read the rest
spa/issues/10991
In We upgraded an old, 3PB large, Elasticsearch cluster without downtime
francoismassot·Sep 22, 2022
(disclaimer: I'm one of the cofounder of Quickwit.io, we are doing log search) (edited to add vector search category and add manticore) When looking at OSS search projects, it's nice to have a rough ideas of the different use cases, here is the list I have in mind: - user facing search (think algolia): elasticsearch[1]/opensearch[2], meilisearch[3], typesense[4] - enterprise search: elasticsearch/opensearch - log search: elasticsearch/opensearch, loki[5], quickwit[6], zincsearch[7] - vector search: Milvus[8], Qdrant[9], Vald[10] Weaviate[11] Vespa.ai[12] is great but I don't really know in which category to put them, user facing and enterprise search seems to work well with them. It's interesting to note that Elasticsearch and Opensearch are general purpose search engine, Solr as well. They are all powered by Lucene, the popular and per
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formant search engine library. Another general purpose search engine is Manticore search[13]. I would love to see some benchmarks by category :) Note: I don't know well ZincSearch and put it in the log search as said on their front page. [1]: https://github.com/elastic/elasticsearch [2]: https://github.com/opensearch-project/OpenSearch [3]: https://github.com/meilisearch/meilisearch/ [4]: https://github.com/typesense/typesense [5]: https://github.com/grafana/loki [6]: https://github.com/quickwit-oss/quickwit [7]: https://github.com/zinclabs/zinc [8]: https://github.com/milvus-io/milvus [9]: https://github.com/qdrant/qdrant [10]: https://github.com/vdaas/vald [11]: https://github.com/semi-technologies/weaviate [12]: https://github.com/vespa-engine/vespa [13]: https://github.com/manticoresoftware/manticoresearch
In ZincSearch – lightweight alternative to Elasticsearch written in Go
garysieling·Oct 29, 2017
For integrating into Solr, I've used Word2vec to improve rankings the synonyms it finds (boosting synonyms by how similar they are to the query). In English Word2vec tends to think plurals are synonyms. I did a talk on this with more details: https://www.slideshare.net/GarySieling/ai-with-the-best-buil... Sense2Vec might also help: https://github.com/explosion/sense2vec There is also a project called Vespa, which looks potentially interesting as a replacement for Lucene - https://github.com/vespa-engine/vespa
In Language Models, Word2Vec, and Efficient Softmax Approximations
aargh_aargh·Sep 27, 2017
$ cloc-git https://github.com/vespa-engine/vespa.git http://cloc.sourceforge.net v 1.60 T=64.10 s (224.5 files/s, 28276.3 lines/s) -------------------------------------------------------------------------------- Language files blank comment code -------------------------------------------------------------------------------- Java 6573 106215 102720 537097 C++ 3209 76542 19178 504855 C/C++ Header 2985 42731 57087 158388 XML 389 705 550 139626 Maven 141 133 244 14096 CMake 450 254
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560 8452 Perl 57 1124 762 7649 Bourne Shell 196 1257 734 6918 Scala 95 1685 617 6378 Teamcenter def 234 1474 3490 2468 Lisp 4 231 403 2118 HTML 16 211 29 1950 C 7 288 198 1432 Python 6 132 66 556 Ruby 9 39 9 294 Bourne Again Shell 3 35 12 182 Pig Latin 9 39 52 54 make 2 22 8 39 Ant 1 9 17 36 YAML 1 9 1 22 DTD 2 6 6 10 -------------------------------------------------------------------------------- SUM: 14389 233141 186743 1392620 --------------------------------------------------------------------------------
In Open-Sourcing Vespa, Yahoo’s Data Processing and Serving Engine
FractalNerve·Sep 27, 2017
May I ask some stupid questions? :/ I don't quite get the diagram of the Vespa Architecture. Is Vespa a middleware between database engine and query parser? This is what puzzles me. If so, are there other such middlewares available for ie. PostgresSQL that allow hooking "Query Templating Models" (that is it?) generated via Machine-Learning Models? Is it way more complicated than that, or did they overengineer the problem into a monolith? EDIT: Looking at https://github.com/vespa-engine/vespa it seems that it is overengineered, or maybe it consists of individual micro-components like node.js, hmm more questions :( Is GraphQL such middleware or lower-level? Does Vespa replace custom Glue-Code between Backend and Frontend that generates such query-sets for content ranking/positioning? Or what exactly does Vespa solve? I'm sorry, I've read th
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e article, but can't say, yep that's what it is! EDIT: How else could you solve what Vespa does using Rust, Go, or C/C++ libraries? A very simple or general direction would be immensely useful to understand Vespa =) The project makes the simultanous impression of an immense engineering feat and at the same time a huge code debt.
In Open-Sourcing Vespa, Yahoo’s Data Processing and Serving Engine

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