Top 10 Qdrant Alternatives & Competitors

(12)4.5 out of 5

Looking for alternatives or competitors to Qdrant? Other important factors to consider when researching alternatives to Qdrant include data analytics and search. The best overall Qdrant alternative is Supabase. Other similar apps like Qdrant are Elasticsearch, Weaviate, Pinecone, and SingleStore. Qdrant alternatives can be found in Vector Database Software but may also be in Enterprise Search Software or Real-time Analytic Database Software.

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Best Paid & Free Alternatives to Qdrant

Supabase
Elasticsearch
Weaviate
Pinecone
SingleStore
Zilliz
CrateDB
PG Vector

Top 10 Alternatives to Qdrant Recently Reviewed By G2 Community

Browse options below. Based on reviewer data, you can see how Qdrant stacks up to the competition, check reviews from current & previous users in industries like Computer & Network Security, Information Technology and Services, and Hospitality, and find the best product for your business.

Supabase

By Supabase

4.7/5

(29)

Product Description

Reviewers say compared to Qdrant, Supabase is:

Better at meeting requirements

Categories in common with Qdrant:

By Elastic

Product Description

Reviewers say compared to Qdrant, Elasticsearch is:

Better at meeting requirements

Better at support

Categories in common with Qdrant:

By Weaviate

Product Description

Weaviate is a cloud-native, real-time vector search engine (aka neural search engine or deep search engine). There are modules for specific use cases such as semantic search, plugins to integrate Weaviate in any application of your choice, and a console to visualize your data. Weaviate is used as a semantic search engine, similar image search engine our automatic classification engine based on the built-in machine learning models. Applications range from product search to CRM classifications. Weaviate has an open-core and a paid service for enterprise SLA usage and custom, industry-specific machine learning models.

Reviewers say compared to Qdrant, Weaviate is:

Better at meeting requirements

Better at support

Categories in common with Qdrant:

Vector Database

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SingleStore

By SingleStore

4.5/5

(118)

Product Description

Reviewers say compared to Qdrant, SingleStore is:

Better at meeting requirements

Better at support

Categories in common with Qdrant:

By ZILLIZ

Product Description

Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more. Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.

Reviewers say compared to Qdrant, Zilliz is:

Better at support

Better at meeting requirements

More usable

Categories in common with Qdrant:

By CrateDB

Product Description

Reviewers say compared to Qdrant, CrateDB is:

Better at support

Better at meeting requirements

Categories in common with Qdrant:

By pgvector

Product Description

PGVector is an open-source extension for PostgreSQL that enables efficient vector similarity searches directly within the database. It allows users to store and query vector data alongside traditional relational data, facilitating tasks such as machine learning model integration, recommendation systems, and natural language processing applications. Key Features and Functionality: - Vector Storage: Supports single-precision, half-precision, binary, and sparse vectors, accommodating diverse data types. - Similarity Search: Offers both exact and approximate nearest neighbor search capabilities, utilizing distance metrics like L2 (Euclidean, inner product, cosine, L1, Hamming, and Jaccard distances. - Indexing: Provides indexing methods such as HNSW (Hierarchical Navigable Small World and IVFFlat (Inverted File with Flat quantization to optimize search performance. - Integration: Compatible with any language that has a PostgreSQL client, enabling seamless incorporation into existing applications. - PostgreSQL Features: Maintains full support for PostgreSQL's ACID compliance, point-in-time recovery, and JOIN operations, ensuring data integrity and reliability. Primary Value and User Solutions: PGVector addresses the challenge of integrating vector similarity search within relational databases by embedding this functionality directly into PostgreSQL. This integration eliminates the need for external systems or complex data pipelines, simplifying architecture and reducing latency. Users can perform efficient similarity searches on vector data stored alongside their relational data, streamlining workflows in applications like recommendation engines, image and text retrieval, and other AI-driven solutions.

Reviewers say compared to Qdrant, PG Vector is:

Better at meeting requirements

Categories in common with Qdrant:

By DataStax

Product Description

Reviewers say compared to Qdrant, DataStax is:

Better at meeting requirements

Better at support

Categories in common with Qdrant:

Vector Database

By KX

4.6/5

(51)

Product Description

KX is maker of kdb+, a time series and vector database, independently benchmarked as the fastest on the market. It can process and analyze time series, historical and vector data at unmatched speed and scale, empowering developers, data scientists, and data engineers to build high-performance data-driven applications and turbo-charge their favorite analytics tools in the cloud, on-premise, or at the edge. For more info visit www.kx.com.

Reviewers say compared to Qdrant, KX is:

Better at meeting requirements

Better at support

Categories in common with Qdrant:

Vector Database