Software Alternatives & Reviews

Lucene VS Qdrant

Compare Lucene VS Qdrant and see what are their differences

Lucene logo Lucene

Search Engines

Qdrant logo Qdrant

Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
  • Lucene Landing page
    Landing page //
    2023-10-01
  • Qdrant Landing page
    Landing page //
    2023-12-20

Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.

Lucene

Pricing URL
-
$ Details
Platforms
-
Release Date
-

Qdrant

$ Details
freemium
Platforms
Linux Windows Kubernetes Docker
Release Date
2021 May

Lucene features and specs

No features have been listed yet.

Qdrant features and specs

  • Advanced Filtering: Yes
  • On-disc Storage: Yes
  • Scalar Quantization: Yes
  • Product Quantization: Yes
  • Binary Quantization: Yes
  • Sparse Vectors: Yes
  • Hybrid Search: Yes
  • Discovery API: Yes
  • Recommendation API: Yes

Lucene videos

Lucene Indexing Tutorial | Solr Indexing Tutorial | Search Engine Indexing | Solr Tutorial |Edureka

More videos:

  • Review - Lucene Search Essentials: Scorers, Collectors and Custom Queries, Mikhail Khludnev
  • Review - Television News Search and Analysis with Lucene/Solr

Qdrant videos

No Qdrant videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to Lucene and Qdrant)
Custom Search Engine
70 70%
30% 30
Search Engine
38 38%
62% 62
Databases
0 0%
100% 100
Custom Search
100 100%
0% 0

Questions and Answers

As answered by people managing Lucene and Qdrant.

Why should a person choose your product over its competitors?

Qdrant's answer:

Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.

What makes your product unique?

Qdrant's answer:

Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.

Which are the primary technologies used for building your product?

Qdrant's answer:

Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.

User comments

Share your experience with using Lucene and Qdrant. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Qdrant should be more popular than Lucene. It has been mentiond 38 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Lucene mentions (21)

  • YaCy, a distributed Web Search Engine, based on a peer-to-peer network
    There are already many project about search: - https://www.marginalia.nu/ - https://searchmysite.net/ - https://lucene.apache.org/ - elastic search - https://presearch.com/ - https://stract.com/ - https://wiby.me/ I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention. I have also been gathering links meta data for some time. Maybe I will use them to feed any... - Source: Hacker News / about 2 months ago
  • Getting started with Elasticsearch + Python
    Elasticsearch is based on Lucene and is used by various companies and developers across the world to build custom search solutions. - Source: dev.to / 3 months ago
  • Tools to use to query and index data?
    Elastic search is kinda heavyweight infra for a small project. Its built on top of apache lucene (https://lucene.apache.org), which you can use directly. Source: 10 months ago
  • Top metrics for Elasticsearch monitoring with Prometheus
    Elasticsearch is based on Lucene, which is built in Java. This means that monitoring the Java Virtual Machine (JVM) memory is crucial to understand the current usage of the whole system. - Source: dev.to / 12 months ago
  • Cross data type search that wasn’t supported well using Elasticsearch
    Apache Lucene which seems to have a lot more features than Elasticsearch. Source: about 1 year ago
View more

Qdrant mentions (38)

  • Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
    Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker. - Source: dev.to / about 14 hours ago
  • Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant
    I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours. - Source: dev.to / 8 days ago
  • Ask HN: Has Anyone Trained a personal LLM using their personal notes?
    I'm currently looking to implement locally, using QDrant [1] for instance. I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2]. [1]. https://qdrant.tech/. - Source: Hacker News / 29 days ago
  • Open-source Rust-based RAG
    There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb. - Source: Hacker News / about 2 months ago
  • Perform Image-Driven Reverse Image Search on E-Commerce Sites with ImageBind and Qdrant
    Initialize the Qdrant Client with in-memory storage. The collection name will be “imagebind_data” and we will be using cosine distance. - Source: dev.to / 2 months ago
View more

What are some alternatives?

When comparing Lucene and Qdrant, you can also consider the following products

Apache Solr - Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and...

Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.

Doxygen - Generate documentation from source code

Weaviate - Welcome to Weaviate

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs