Comparison between ChromaDB , Oracle 26ai, PG_Vector , Milvus (Vector database)

 🚀 Tired of complex vector database setups? 

Let's talk about ChromaDB... and why enterprise solutions like Oracle still lead the pack!

In the rapidly evolving world of Generative AI and RAG (Retrieval-Augmented Generation), choosing the right vector store is crucial.

ChromaDB: The Developer's Best Friend

ChromaDB is a fantastic choice for developers and smaller projects, prioritizing simplicity and developer velocity.

1.    Open-Source & Embeddable: It's open-source and can be run entirely embedded within your Python application, making it incredibly lightweight and perfect for local development and prototyping.

2.    Focus on Simplicity: It's designed to be easy to get started with, reducing the "hard parse" of setting up complex infrastructure. This speed-to-market is a huge win for developers building RAG pipelines.

Oracle AI Vector Search: The Enterprise Powerhouse

However, when the scale, security, and complexity of enterprise data come into play, solutions like Oracle AI Vector Search in Oracle Database 26ai offer distinct advantages over standalone vector databases like ChromaDB:

• Unified Data Model: Oracle excels by allowing you to combine semantic search on unstructured data (vectors) with traditional relational search on business data. This unified approach eliminates data silos and simplifies application development.
• Enterprise-Grade Features: Oracle Database 26ai offers a much broader range of high availability, disaster recovery, and robust security options that are non-negotiable for mission-critical applications.
• Scalability and Reliability: Leveraging decades of database expertise, Oracle provides proven, massive scalability and reliability that far exceed what a lightweight, embedded solution like ChromaDB is designed for.

 

The Takeaway:

If your priority is a lightweight, self-hostable, and developer-friendly tool for quick prototyping, ChromaDB is a great starting point. But for enterprise-grade, secure, and highly scalable applications that require combining vector search with structured business data, Oracle's integrated solution is the clear winner.

 

A Comparison based on:

https://medium.com/@isakulaksiz.ce/vector-database-loadtest-comparison-milvus-oracle-26ai-and-pgvector-a2c4cf3577fe

 

⚡️ Vector Database Showdown: Milvus vs. Oracle 26ai vs. pgvector!

Choosing the right vector database is critical for the performance of your RAG and Generative AI applications. A recent load test comparing Milvus, Oracle 26ai (AI Vector Search), and pgvector sheds light on which solution truly delivers on speed and relevance.

The key takeaway from the comparison is clear: Milvus demonstrated superior performance in search speed under various load conditions.

Key Performance Findings:

Metric	Milvus (HNSW)	Oracle 26ai (HNSW)	pgvector (HNSW)
Search Speed	Fastest	Significantly Slower	Significantly Slower
Speed Comparison	Baseline	~9x Slower	~10x Slower
Relevance	Most Relevant	Superficial/General	N/A
Insert Time	Fastest (with GPU)	Slowest	Middle

Note: Comparisons are based on the load test results using the HNSW index.

Why Milvus Pulled Ahead:

1.    Speed Dominance: Milvus was found to be up to 9x faster than Oracle 26ai and 10x faster than pgvector in search operations, particularly when utilizing the HNSW (Hierarchical Navigable Small World) index.

2.    Relevance: Beyond just speed, Milvus with HNSW returned the most relevant chunks during the retrieval process, a crucial factor for reducing LLM hallucinations.

3.    Efficient Ingestion: For data ingestion, the Milvus GPU setup proved to have the fastest vector embedding and insert time.

The Trade-Offs:

While Milvus excels in raw vector search performance, it's important to remember the trade-offs:

• Oracle 26ai and pgvector offer the advantage of unified data platforms, allowing you to combine vector search with traditional relational data, which is essential for many enterprise applications.
• The performance gap highlights that specialized vector databases like Milvus are currently optimized for the highest-speed vector operations.

What does this mean for your stack? If maximum vector search speed and relevance are your top priority, Milvus is a strong contender. If you need the security, stability, and unified data model of a traditional database, Oracle or pgvector might be the necessary compromise.