Zilliz Cloud vs MyScale Choosing the Right Vector Database for Your AI Apps
What is a Vector Database?
Before we compare Zilliz Cloud and MyScale, let's first explore the concept of vector databases.
A vector database is specifically designed to store and query high-dimensional vectors, which are numerical representations of unstructured data. These vectors encode complex information, such as the semantic meaning of text, the visual features of images, or product attributes. By enabling efficient similarity searches, vector databases play a pivotal role in AI applications, allowing for more advanced data analysis and retrieval.
Common use cases for vector databases include e-commerce product recommendations, content discovery platforms, anomaly detection in cybersecurity, medical image analysis, and natural language processing (NLP) tasks. They also play a crucial role in Retrieval Augmented Generation (RAG), a technique that enhances the performance of large language models (LLMs) by providing external knowledge to reduce issues like AI hallucinations.
There are many types of vector databases available in the market, including:
- Purpose-built vector databases such as Milvus, Zilliz Cloud (fully managed Milvus)
- Vector search libraries such as Faiss and Annoy.
- Lightweight vector databases such as Chroma and Milvus Lite.
- Traditional databases with vector search add-ons capable of performing small-scale vector searches.
Zilliz Cloud is a purpose-built vector database. MyScale is a database built on ClickHouse that combines vector search and SQL analytics with vector search capabilities as an add-on. This post compares their vector search capabilities.
Zilliz Cloud: Overview and Core Technology
Zilliz Cloud is a fully managed vector database service built on top of the open-source Milvus engine. It helps developers and organizations to handle large scale AI applications by storing, managing and searching vector embeddings efficiently. It takes care of infrastructure for you, so you can focus on building AI features instead of managing databases.
One of the key advantages of Zilliz Cloud is the automatic performance optimization. The system has AutoIndex technology which will choose the best indexing method for your data and use case. So you don’t have to spend time tuning parameters or comparing different index types. The platform also uses IVF (Inverted File) and graph-based techniques to speed up similarity search across large datasets.
The platform has enterprise features. You can deploy your vector databases across AWS, Azure or Google Cloud, with options to use Zilliz’s fully managed service or bring your own cloud account (BYOC). For organizations that handle sensitive data, Zilliz Cloud has security controls like encryption, access management and compliance tools. The system also supports different consistency levels so you can balance between fast updates and strong data consistency based on your needs.
Cost management is another important aspect of Zilliz Cloud. The platform uses tiered storage to automatically move less accessed data to cheaper storage options, so you can reduce cost without affecting performance. You can also choose compute resources that match your workload - for example, use more powerful instances for heavy processing tasks and lighter ones for simple queries. This flexibility helps you to optimize your spending while maintaining good performance.
For AI applications that need to search different types of data together, Zilliz Cloud supports hybrid search. You can search across text embeddings, image vectors and other data types in a single query. The platform also supports various similarity metrics like Cosine, Euclidean and Inner Product so it’s suitable for different machine learning models and use cases. As your data grows, the system can scale horizontally by adding more resources automatically so you can maintain good performance even under heavy workload.
What is MyScale? Overview and Core Technology
MyScale is a cloud based database built on top of the open source ClickHouse database, designed for AI and machine learning workloads. It can handle structured and vector data and real time analytics and machine learning. MyScale is focused on time series, vector search and full text search so it’s good for real time processing and AI driven insights. By using ClickHouse architecture, MyScale is high performance and scalable for AI.
One of the key features of MyScale is native SQL support which simplifies AI driven queries by integrating vector search, full text search and traditional SQL queries in one system. This reduces the need for multiple tools and makes it scalable for AI. MyScale supports and manages analytical processing of both structured and vectorized data on one platform using OLAP database architecture to operate on vectorized data. Developers can interact with MyScale using SQL so it’s accessible to all programmers familiar with relational databases.
MyScale has multiple vector index types and similarity metrics to support different use cases. It supports common distance metrics like Euclidean distance (L2), inner product (IP) and cosine similarity. The database has multiple indexing algorithms: MSTG (Multi-Scale Tree Graph), ScaNN, IVFFLAT, IVFPQ, IVFSQ and HNSW, each with its own set of parameters to tune. MyScale’s proprietary MSTG vector engine uses NVMe SSDs to increase data density so it outperforms specialized vector databases in both performance and cost.
By combining the functionality of an SQL database, vector database and full text search engine into one system MyScale reduces infrastructure and maintenance costs. This unification allows for joint data queries and analytics and a single data foundation for AI applications. MyScale also has MyScale Telemetry for full observability of LLM systems so you can monitor and debug efficiently. As data gets more complex MyScale is a future proof solution that can handle newer data modalities and database sizes while keeping computing performance and integration between different data types.
Key Differences
When it comes to vector database for AI applications, Zilliz Cloud and MyScale are two different approaches to vector search. Each platform is built on different foundation - Zilliz Cloud is built on top of open-source Milvus engine, while MyScale is built on top of ClickHouse architecture. This fundamental difference affects how each platform processes data and search.
Zilliz Cloud focuses on specialized vector operations with built-in optimizations. AutoIndex removes the complexity of choosing and tuning index types by automatically selecting the right one for your data and use case. IVF and graph-based methods for similarity search, support standard metrics like cosine similarity, Euclidean distance and inner product.
MyScale takes a different approach by integrating SQL, vector search and full-text search into one system. This unified platform allows developers to use SQL syntax for both traditional queries and vector operations. MyScale offers multiple indexing options, including their proprietary MSTG vector engine that uses NVMe SSDs for higher data density. Other options include ScaNN, IVFFLAT, IVFPQ, IVFSQ and HNSW, so developers have flexibility to optimize their search.
When it comes to data management, each platform has its advantages. Zilliz Cloud is good at pure vector operations and supports hybrid search across different data types. You can search text embeddings and image vectors in one query. The platform handles horizontal scaling automatically and offers deployment options on AWS, Azure or Google Cloud, with choices between fully managed services or bring your own cloud account.
MyScale’s unified approach to structured and vector data is unique. By using SQL syntax, developers can combine traditional queries with vector operations seamlessly. This is particularly useful for applications that need both analytical capabilities and vector search. The ClickHouse foundation provides strong real-time processing and analytics support.
Cost management features are different between the platforms. Zilliz Cloud uses tiered storage, automatically moves less accessed data to cheaper storage. Users can also choose compute resources that match their workload, use more powerful instances for heavy processing and lighter ones for simple queries. MyScale approaches cost efficiency through infrastructure consolidation, reduces cost by combining multiple database functionalities into one system. Their MSTG vector engine also helps to optimize storage cost.
Both platforms have comprehensive security features. Zilliz Cloud provides encryption, access management and compliance tools, with different consistency levels to balance between update speed and data consistency. MyScale has standard database security features and MyScale Telemetry for system monitoring.
When to Choose Each
Zilliz Cloud is for when you need pure vector search with minimal config overhead. It’s the one to choose for companies building recommendation systems, image similarity search or large scale AI applications that require auto performance optimization. It’s great for teams that want to focus on building AI features without managing complex infrastructure especially when dealing with multiple vector types or hybrid search across different data modalities.
MyScale is for when your application needs to combine SQL operations with vector search. It’s the one to choose for companies that handle time-series data with vector operations, need real-time analytics or want to have one system for both structured and vector data. It’s great for teams with SQL expertise building applications that require complex queries combining traditional database operations with vector similarity search.
Conclusion
The choice between Zilliz Cloud and MyScale is all about different approaches to vector search. Zilliz Cloud is great for specialized vector operations, auto optimization and managed infrastructure, for teams that want a dedicated vector search solution. MyScale is great for unified approach, combining SQL with vector operations, for applications that need both traditional database features and vector search. Your decision should be based on your requirements: consider your data types (pure vectors vs mixed data), query patterns (specialized vector search vs combined SQL and vector operations), team expertise (infrastructure management vs SQL development), and scaling needs (auto vs manual optimization). The right choice depends on these factors and how they match your application’s goals and your team’s capabilities.
Read this to get an overview of Zilliz Cloud and MyScale but to evaluate these you need to evaluate based on your use case. One tool that can help with that is VectorDBBench, an open-source benchmarking tool for vector database comparison. In the end, thorough benchmarking with your own datasets and query patterns will be key to making a decision between these two powerful but different approaches to vector search in distributed database systems.
Using Open-source VectorDBBench to Evaluate and Compare Vector Databases on Your Own
VectorDBBench is an open-source benchmarking tool for users who need high-performance data storage and retrieval systems, especially vector databases. This tool allows users to test and compare different vector database systems like Milvus and Zilliz Cloud (the managed Milvus) using their own datasets and find the one that fits their use cases. With VectorDBBench, users can make decisions based on actual vector database performance rather than marketing claims or hearsay.
VectorDBBench is written in Python and licensed under the MIT open-source license, meaning anyone can freely use, modify, and distribute it. The tool is actively maintained by a community of developers committed to improving its features and performance.
Download VectorDBBench from its GitHub repository to reproduce our benchmark results or obtain performance results on your own datasets.
Take a quick look at the performance of mainstream vector databases on the VectorDBBench Leaderboard.
Read the following blogs to learn more about vector database evaluation.
Further Resources about VectorDB, GenAI, and ML
- What is a Vector Database?
- Zilliz Cloud: Overview and Core Technology
- What is MyScale? Overview and Core Technology
- Key Differences
- Using Open-source VectorDBBench to Evaluate and Compare Vector Databases on Your Own
- Further Resources about VectorDB, GenAI, and ML
Content
Start Free, Scale Easily
Try the fully-managed vector database built for your GenAI applications.
Try Zilliz Cloud for FreeThe Definitive Guide to Choosing a Vector Database
Overwhelmed by all the options? Learn key features to look for & how to evaluate with your own data. Choose with confidence.