Running SQL Server 2022 Anywhere

Leverage the power of RustFS to run SQL Server 2022 on any cloud (public, private, or edge) using external table functions and PolyBase.

Any to Any, All the Time

Use SQL Server 2022 data cloud to query and analyze multiple data sources residing on RustFS. Now enterprises can query data residing on RustFS from any SQL Server instance (in public cloud, private cloud, or even streaming edge instances).

Supported Deployment Environments

RustFS integration with SQL Server 2022 supports the following deployment environments:

• AWS: Amazon Web Services cloud environment
• GCP: Google Cloud Platform
• Azure: Microsoft Azure cloud platform
• Tanzu: VMware Tanzu container platform
• OpenShift: Red Hat OpenShift container platform
• HPE Ezmeral: HPE's container platform
• SUSE Rancher: SUSE's Kubernetes management platform
• Traditional Bare Metal Deployment: On-premises data center environments

Unified Data Access

Through RustFS's unified S3-compatible interface, SQL Server 2022 can:

• Access data across multiple cloud environments
• Eliminate data silos
• Provide consistent query experience
• Reduce data integration complexity

Connect to Data, Don't Move It

Using external tables, enterprises can enjoy the full functionality of SQL Server without incurring the cost or coordination challenges of moving data.

PolyBase Feature Advantages

PolyBase functionality allows users to query data directly from SQL Server and most other database installations using Transact-SQL:

Supported Data Sources

• SQL Server: On-premises and cloud instances
• Oracle: Enterprise-grade relational database
• Teradata: Big data analytics platform
• MongoDB: NoSQL document database
• S3 API: Access object storage through RustFS

Core Advantages

1. Zero Data Movement: Direct querying of remote data sources
2. Unified Query Language: Use familiar T-SQL syntax
3. Real-time Data Access: No need to pre-load data
4. Reduced Storage Costs: Avoid duplicate data storage

Data Silo Integration

RustFS provides unique capabilities for accessing all hyperscale cloud environments. The combination of SQL Server 2022 and RustFS enables enterprises to:

• Access data scattered across different systems
• Gain comprehensive insights from data silos
• Achieve unified data view
• Simplify complex data integration scenarios

Massive Scale Performance

Massive scale performance solutions for all enterprise data.

Performance Characteristics

With this new capability, enterprises can use SQL Server 2022 for all organizational data:

Unlimited Data Scale

• Location Agnostic: Data can be located anywhere
• Unlimited Scale: Support for multi-petabyte data storage
• Fast Queries: High-speed queries for massive datasets
• Concurrent Processing: Support for multi-user concurrent access

Performance Optimization

With RustFS's industry-leading performance characteristics:

1. High Throughput: Optimized data transfer speeds
2. Low Latency: Fast response to query requests
3. Intelligent Caching: Improve performance for frequently accessed data
4. Load Balancing: Automatic query load distribution

Resource Utilization Enhancement

This means higher utilization:

• SQL Server Utilization: More fully utilize existing SQL Server investments
• RustFS Instance Utilization: Maximize storage resource value
• Enterprise Data Utilization: Unlock the full value of data

Backup and Recovery

Backup and restore like you've always dreamed of.

Core Use Cases

One of the core use cases for SQL Server 2022 and RustFS is backup and restore:

Diverse Configuration Support

• Multiple Architectures: Support different deployment architectures
• Flexible Configuration: Adapt to various business needs
• Scalability: Scale with business growth

Fast Recovery Capabilities

RustFS's industry-leading throughput characteristics:

1. Time Compression: Reduce weeks of recovery time to hours
2. High Availability: Ensure business continuity
3. Data Integrity: Guarantee backup data integrity
4. Automated Processes: Reduce manual intervention

Backup Strategy Optimization

Effective backup strategies include:

• Incremental Backup: Only backup changed data
• Differential Backup: Changes based on last full backup
• Full Backup: Regular complete data backup
• Instant Recovery: Fast recovery of critical business data

Secure and Available

To ensure the right data is available to the right users, fine-grained access control must be implemented on these multi-cloud data lakes.

Identity Authentication and Authorization

Third-Party IDP Integration

RustFS can integrate with third-party identity providers (IDPs):

• Unified Identity Management: Centralized user identity management
• Single Sign-On (SSO): Simplified user access experience
• Multi-Factor Authentication (MFA): Enhanced security
• Role Mapping: Automatic assignment of appropriate permissions

Access Control Mechanisms

Ensure access to object storage is limited to those who need it:

1. Principle of Least Privilege: Only grant necessary permissions
2. Regular Permission Reviews: Ensure permission timeliness
3. Access Logging: Complete audit trails
4. Anomaly Detection: Identify abnormal access behavior

Policy-Based Access Control (PBAC)

Fine-Grained Permission Management

RustFS's sophisticated PBAC functionality ensures:

• Resource-Level Control: Precise permissions to specific resources
• Dynamic Permission Assignment: Adjust permissions based on context
• Policy Inheritance: Simplify permission management
• Compliance Support: Meet regulatory requirements

Security Assurance

• Data Encryption: Encryption protection during transmission and storage
• Network Isolation: Secure network communication
• Threat Detection: Real-time security threat monitoring
• Incident Response: Rapid response to security incidents

Resilience

SQL Server is one of the most widely used analytics tools in enterprises, making it a mission-critical application.

Disaster Recovery Capabilities

Continuous Data Replication

SQL Server 2022 allows continuous data replication to and from the cloud:

• Real-time Synchronization: Ensure data is up-to-date
• Bidirectional Replication: Support active-active deployment
• Conflict Resolution: Automatically handle data conflicts
• Failover: Quick switch to backup systems

Tiered Storage Strategy

The combination with RustFS allows:

1. Fast Storage Tier: NVMe high-speed storage
2. Warm Storage Tier: Balance performance and cost
3. Cold Storage Tier: Long-term archival storage
4. Automatic Tiering: Intelligent data movement

Data Processing Capabilities

Multiple Processing Methods

Enterprises can read, write, and process big data using multiple methods:

• Transact-SQL: Traditional SQL query language
• Spark Libraries: Big data processing framework
• Hybrid Analytics: Combine relational and non-relational data
• Real-time Processing: Stream data processing capabilities

High Availability Architecture

• Multi-site Deployment: Cross-regional data distribution
• Active-Active Replication: Provide highest availability
• Strict Consistency: Ensure data consistency
• Cloud Disaster Recovery: Resist complete cloud failures

Streaming Edge

By adding external table functionality, enterprises can now set up streaming pipelines to save data on RustFS - in the cloud or on-premises.

Real-time Data Processing

Streaming Data Pipelines

• Real-time Data Ingestion: Continuously receive streaming data
• Data Preprocessing: Clean and transform data
• Storage Optimization: Efficient data storage
• Query Optimization: Query optimization for streaming data

Real-time Query Capabilities

SQL Server can be configured to execute queries on this data in real-time:

1. Eliminate Batch Imports: No need to wait for batch processing
2. Instant Insights: Real-time business insights
3. Reduced Latency: Minimize data processing delays
4. Enhanced Experience: Add new dimensions to SQL Server

Edge Computing Advantages

Edge Deployment Characteristics

• Low Latency Processing: Process data close to source
• Bandwidth Optimization: Reduce data transmission
• Offline Capabilities: Support intermittent connectivity
• Local Intelligence: Edge intelligent decision-making

Application Scenarios

• IoT Data Processing: Internet of Things device data
• Real-time Monitoring: System status monitoring
• Predictive Maintenance: Equipment failure prediction
• Smart Manufacturing: Production process optimization

Cloud as Operating Model

Cloud operating model starting from S3.

Cloud Operations Characteristics

RustFS adheres to the cloud operating model:

Core Technology Stack

• Containerization: Containerized application deployment
• Orchestration: Kubernetes container orchestration
• Automation: Automated operations management
• API-Driven: Complete API interface
• S3 Compatibility: Standard S3 API support

Unified Interface Advantages

Provides unified interface across clouds and storage types:

1. Simplified Development: Unified development interface
2. Reduced Learning Costs: Standardized operation methods
3. Improved Portability: Cross-cloud application migration
4. Reduced Lock-in: Avoid vendor lock-in

AI/ML Framework Compatibility

Broad Framework Support

Since most AI/ML frameworks and applications are designed to use S3 API:

• TensorFlow: Google's machine learning framework
• PyTorch: Facebook's deep learning framework
• Scikit-learn: Python machine learning library
• Apache Spark: Big data processing engine

Developer Validation

With over 1.3 billion Docker pulls:

• Most Developer Validated: Extensive developer community
• 24/7/365 Validation: Continuous compatibility validation
• Best Compatibility: Industry-best compatibility record
• Production Ready: Large-scale production validated

Data Management Flexibility

This compatibility ensures:

• AI Workload Access: Seamless access to stored data
• Cloud Infrastructure Agnostic: Independent of specific cloud environments
• Flexible Data Approaches: Adapt to different data processing needs
• Cross-Cloud Environment Processing: Support multi-cloud data processing

Edge AI Storage

At the edge, network latency, data loss, and software bloat degrade performance.

Edge Optimization Features

Performance Advantages

RustFS is the world's fastest object storage:

• Less than 100 MB: Extremely small binary files
• Any Hardware: Can be deployed on any hardware
• High Performance: Optimized edge performance
• Low Resource Consumption: Minimal system requirements

Intelligent Features

RustFS's advanced features:

1. Bucket Notifications: Storage bucket event notifications
2. Object Lambda: Object processing functions
3. Real-time Inference: Instant data processing
4. Automatic Triggers: Event-based automatic processing

Edge Application Scenarios

Mission-Critical Applications

• Airborne Object Detection: High-altitude drone applications
• Traffic Trajectory Prediction: Autonomous vehicles
• Industrial Control: Real-time industrial control systems
• Security Monitoring: Real-time security monitoring

Technical Characteristics

RustFS's AI storage features:

• Fast Response: Millisecond response times
• Fault Tolerance: High reliability design
• Simple Deployment: Simplified deployment process
• Edge Optimization: Optimized for edge scenarios

Lifecycle Management for ML/AI Workloads

Modern AI/ML workloads require complex lifecycle management.

Automated Data Management

Core Functions

RustFS's lifecycle management capabilities:

• Automated Tasks: Automatically execute data management tasks
• Storage Optimization: Optimize storage efficiency
• Reduced Overhead: Lower operational overhead
• Intelligent Tiering: Automatic data tiering

Cost Optimization Strategies

With lifecycle policies:

1. Automatic Migration: Migrate infrequently accessed data to low-cost storage
2. Resource Release: Free resources for active workloads
3. Storage Tiering: Multi-tier storage architecture
4. Cost Control: Effective storage cost control

ML/AI Specialized Functions

Developer Experience

These features ensure AI/ML practitioners can:

• Focus on Core: Focus on model training and development
• Automatic Management: RustFS intelligently manages data
• Performance Enhancement: Improve overall workflow performance
• Cost Effectiveness: Achieve maximum cost effectiveness

Compliance Support

Lifecycle management layer:

• Enforce Policies: Enforce retention and deletion policies
• Regulatory Compliance: Ensure compliance with regulations
• Audit Trails: Complete operation records
• Automated Compliance: Automated compliance processes

Object Retention for AI/ML Workflows

Compared to AI/ML, fewer workloads depend more on when things happen.

Advanced Object Retention

Core Guarantees

Addressed through advanced object retention features:

• Data Integrity: Ensure integrity of stored data
• Compliance Requirements: Meet regulatory compliance requirements
• Time Sensitivity: Handle time-related business needs
• Data Consistency: Maintain data consistency

Retention Policy Implementation

By implementing retention policies, RustFS can help organizations:

1. Model Consistency: Maintain data consistency for AI/ML models and datasets
2. Prevent Accidental Deletion: Avoid accidental or unauthorized deletion
3. Prevent Modification: Protect data from unauthorized modification
4. Version Control: Maintain data version history

Data Governance Advantages

Governance Framework

This feature is crucial for:

• Data Governance: Establish comprehensive data governance framework
• Regulatory Compliance: Meet various regulatory requirements
• Experiment Reproducibility: Ensure AI/ML experiment reproducibility
• Data Lineage: Complete data lineage tracking

Guarantee Mechanisms

Guarantee critical data:

• Specific Duration: Remain accessible for specified time
• Data Immutability: Ensure data is not modified
• Precise Training: Support precise model training
• Reliable Analysis: Provide reliable data analysis foundation

Data Protection for Core AI Datasets

RustFS provides comprehensive data protection through different feature quantities.

Data Redundancy and Fault Tolerance

Protection Mechanisms

• Erasure Coding: Efficient data redundancy mechanism
• Site Replication: Cross-site data replication
• Data Redundancy: Ensure redundant data storage
• Fault Tolerance: Prevent hardware failures or data corruption

Failure Recovery

Automatically handle various failure scenarios:

1. Hardware Failures: Automatic detection and recovery
2. Data Corruption: Real-time detection and repair
3. Network Failures: Automatic recovery from network interruptions
4. Site Failures: Cross-site failover

Data Encryption Protection

Encryption Mechanisms

RustFS supports multi-level data encryption:

• Encryption at Rest: Encryption protection for stored data
• Encryption in Transit: Encryption during data transmission
• Key Management: Secure key management mechanisms
• Compliance Encryption: Encryption standards meeting compliance requirements

Access Control

• Unauthorized Access Protection: Prevent unauthorized data access
• Authentication: Enforce authentication mechanisms
• Permission Control: Fine-grained permission control
• Access Monitoring: Real-time access behavior monitoring

Identity and Access Management (IAM)

IAM Support

RustFS's IAM support enables organizations to:

• Access Control: Control access to AI storage data
• User Management: Unified user management
• Application Authorization: Application access control
• Permission Assignment: Flexible permission assignment mechanisms

Security Assurance

Ensure only authorized users or applications can:

1. Access Data: Secure data access
2. Modify Data: Controlled data modification
3. Delete Data: Secure data deletion
4. Manage Permissions: Permission management operations

Full Lifecycle Protection

Comprehensive Protection Mechanisms

RustFS provides comprehensive data protection mechanisms:

• Integrity Protection: Maintain AI dataset integrity
• Availability Assurance: Ensure high data availability
• Confidentiality Protection: Protect data confidentiality
• Lifecycle Coverage: Cover entire data lifecycle

Through deep integration of SQL Server 2022 with RustFS, enterprises can build a powerful, secure, high-performance modern data platform supporting comprehensive needs from traditional relational data processing to the latest AI/ML workloads.