Amazon EC2 Part 4-Hindi/Urdu | Memory Optimized Instance & Storage optimized Instance | TYPES OF EC2
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Amazon EC2 Part 4-Hindi/Urdu | Memory Optimized Instance & Storage optimized Instance | TYPES OF EC2
Storage optimized instances:-----
Storage optimized instances are designed for workloads that require high, sequential read and write access to very large data sets on local storage. They are optimized to deliver tens of thousands of low-latency, random I/O operations per second (IOPS) to applications.
D2 instances
These instances are well suited for the following:
Massive parallel processing (MPP) data warehouse
MapReduce and Hadoop distributed computing
Log or data processing applications
D3 and D3en instances
These instances offer scale out of instance storage and are well suited for the following:
Distributed file systems for Hadoop workloads
File storage workloads such as GPFC and BeeFS
Large data lakes for HPC workloads
H1 instances
These instances are well suited for the following:
Data-intensive workloads such as MapReduce and distributed file systems
Applications requiring sequential access to large amounts of data on direct-attached instance storage
Applications that require high-throughput access to large quantities of data
I3 and I3en instances
These instances are well suited for the following:
High frequency online transaction processing (OLTP) systems
Relational databases
NoSQL databases
Cache for in-memory databases (for example, Redis)
Data warehousing applications
Distributed file systems
Bare metal instances provide your applications with direct access to physical resources of the host server, such as processors and memory.
Memory Optimized :------
Memory optimized instances are designed to deliver fast performance for workloads that process large data sets in memory.
R5, R5a, R5b, and R5n instances
These instances are well suited for the following:
High-performance, relational (MySQL) and NoSQL (MongoDB, Cassandra) databases.
Distributed web scale cache stores that provide in-memory caching of key-value type data (Memcached and Redis).
In-memory databases using optimized data storage formats and analytics for business intelligence (for example, SAP HANA).
Applications performing real-time processing of big unstructured data (financial services, Hadoop/Spark clusters).
High-performance computing (HPC) and Electronic Design Automation (EDA) applications.
Bare metal instances, such as r5.metal, provide your applications with direct access to physical resources of the host server, such as processors and memory.