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Description
Amazon ElastiCache enables users to effortlessly establish, operate, and expand widely-used open-source compatible in-memory data stores in the cloud environment. It empowers the development of data-driven applications or enhances the efficiency of existing databases by allowing quick access to data through high throughput and minimal latency in-memory stores. This service is particularly favored for various real-time applications such as caching, session management, gaming, geospatial services, real-time analytics, and queuing. With fully managed options for Redis and Memcached, Amazon ElastiCache caters to demanding applications that necessitate response times in the sub-millisecond range. Functioning as both an in-memory data store and a cache, it is designed to meet the needs of applications that require rapid data retrieval. Furthermore, by utilizing a fully optimized architecture that operates on dedicated nodes for each customer, Amazon ElastiCache guarantees incredibly fast and secure performance for its users' critical workloads. This makes it an essential tool for businesses looking to enhance their application's responsiveness and scalability.
Description
Sangfor aStor represents an innovative software-defined storage solution that consolidates block, file, and object storage into a cohesive, elastically scalable resource pool, utilizing a fully symmetrical distributed architecture to facilitate on-demand provisioning of high-performance and cost-effective storage tiers tailored to various service needs. It can be deployed as either an integrated hardware-software system or as standalone software, with the ability to scale from a minimal setup of three commodity x86 nodes to expansive cloud-scale clusters comprising thousands of nodes, allowing for EB-level capacity growth. The system's multi-node parallel processing and intelligent caching mechanisms—including RDMA, SSD hot-data caching, and layering—achieve exceptional throughput, IOPS, and performance with small I/O operations, significantly enhancing cache hit rates to 90% and improving small I/O processing by as much as 65%. Additionally, its distributed metadata management ensures the seamless handling of billions of files without any significant latency, making it a robust solution for modern storage challenges. Overall, Sangfor aStor stands out as a versatile and powerful option for organizations looking to optimize their storage infrastructure.
API Access
Has API
API Access
Has API
Integrations
AWS App Mesh
AWS Virtual Waiting Room
Amazon EC2
Apono
Archera
Argonaut
Centreon
Feast
Heimdall Data
KeyDB
Integrations
AWS App Mesh
AWS Virtual Waiting Room
Amazon EC2
Apono
Archera
Argonaut
Centreon
Feast
Heimdall Data
KeyDB
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/elasticache/
Vendor Details
Company Name
Sangfor
Founded
2000
Country
China
Website
www.sangfor.com/cloud-and-infrastructure/products/astor-enterprise-data-storage-solution
Product Features
Database
Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization
Infrastructure-as-a-Service (IaaS)
Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring
RDBMS
Backup
Data Migration
Monitoring
Performance Analysis
Queries
Storage Optimization