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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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8 Top key points in Apache Cassandra in the age of Big data

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Hadoop Questions
(Hadoop questions...)
Decentralized: Every knot within the array has the similar part. There is no sole point of letdown. Data is dispersed athwart the array (so every one node holds dissimilar data), however there is no principal as any knot may facility whatever appeal.

Supports replication and multi information centre replication: Replication strategic plans are configurable. Cassandra is developed like a dispersed configuration, for distribution of great numerals of nodes athwart numerous information hubs. Key attributes of Cassandra’s dispersed design are especially custom-made for multiple-data centre distribution, for superfluity, for a procedure by which a system automatically transfers control to a duplicate system when it detects a fault or failure and calamity recuperation.

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Scalability: Read and record output either rise linearly as spic-and-span devices are appended, with no layoff either discontinuity to applications.

Fault-tolerant: Data is automatedly cloned to numerous knots for Fault-tolerance. Replication athwart numerous information hubs is maintained. Failed knots may be substituted with no layoff.

 Tunable consistency: Writes and peruses proffer a tunable layer of consistence, altogether the way as of ‘writes not ever fail’ to ‘block for altogether replicas to be readable’, with the minimum number layer in the mid.

MapReduce support: Cassandra has Hadoop incorporation, with MapReduce aid. There is aid as well for Apache Pig and Apache Hive.

Query language: CQL (Cassandra Query Language) was instituted, a SQL-like alternate to the customary RPC user interface. Language drivers are accessible aimed at Java (JDBC), Python (DBAPI2) and Node.JS (Helenus).

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