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What is Zilliz Cloud?

While working with structured data is relatively straightforward, a significant majority—over 80%—of data generated today is unstructured, necessitating a different methodology. Machine learning plays a crucial role by transforming unstructured data into high-dimensional numerical vectors, which facilitates the discovery of underlying patterns and relationships within that data. However, conventional databases are not designed to handle vectors or embeddings, falling short in addressing the scalability and performance demands posed by unstructured data. Zilliz Cloud is a cutting-edge, cloud-native vector database that efficiently stores, indexes, and searches through billions of embedding vectors, enabling sophisticated enterprise-level applications like similarity search, recommendation systems, and anomaly detection. Built upon the widely-used open-source vector database Milvus, Zilliz Cloud seamlessly integrates with vectorizers from notable providers such as OpenAI, Cohere, and HuggingFace, among others. This dedicated platform is specifically engineered to tackle the complexities of managing vast numbers of embeddings, simplifying the process of developing scalable applications that can meet the needs of modern data challenges. Moreover, Zilliz Cloud not only enhances performance but also empowers organizations to harness the full potential of their unstructured data like never before.

What is Raijin ?

To tackle the issues associated with limited data, the Raijin Database implements a straightforward JSON structure for its data entries. This database leverages SQL for querying while successfully navigating some of its traditional limitations. By utilizing data compression methods, it not only saves storage space but also boosts performance, especially with modern CPU technologies. Numerous NoSQL solutions often struggle with efficiently executing analytical queries or entirely lack this capability. In contrast, Raijin DB supports group by operations and aggregations using conventional SQL syntax. Its vectorized execution, paired with cache-optimized algorithms, allows for the effective handling of large datasets. Furthermore, the incorporation of advanced SIMD instructions (SSE2/AVX2) along with a contemporary hybrid columnar storage system ensures that CPU cycles are used efficiently. As a result, this leads to outstanding data processing performance that surpasses many other options, particularly those created in higher-level or interpreted programming languages that may falter with extensive data volumes. This remarkable efficiency establishes Raijin DB as a robust choice for users who require quick and effective analysis and manipulation of large datasets, making it a standout option in the data management landscape.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Azure Marketplace
ChatGPT
ChatGPT Plus
ChatGPT Pro
Cohere
Coral
Google Cloud Platform
HoneyHive
Hugging Face
IBM watsonx.data
Java
Milvus
OpenAI
PyTorch

Integrations Supported

NXLog

API Availability

Has API

API Availability

Pricing Information

$0
Zilliz Cloud on AWS
Compute Unit (CU) - $0.259 / hour
Storage - $0.025 / GB per month

Zilliz Cloud on Google Cloud
Compute Unit (CU) - $0.215 / hour
Storage - $0.02 / GB per month
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

Zilliz

Date Founded

2017

Company Location

United States

Company Website

zilliz.com

Company Facts

Organization Name

RAIJINDB

Company Location

Hungary

Company Website

www.raijindb.com

Categories and Features

Anomaly Detection

Not specified

Context Engineering

Not specified

Database

Backup and Recovery
Data Migration
Data Search
Data Security
Queries

Vector Databases

Not specified

Categories and Features

Database

Data Security
Database Conversion
Mobile Access
NOSQL
Queries

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