Less expensive way to manage database needs for companies.
Offers simplicity, automation, and within AWS.
Features:
Supports MySQL, SQL Server, and Oracle. Popular relational databases.
Any required patches and updates to the database software are made by RDS.
RDS makes backups of the database according to a schedule you set. All backups are stored in S3, where they can be retrieved at any time. Amazon also performs EBS snashots to enable database transference.
RDS can be run on different instance types. This flexibility ensures that you have sufficient processing power to support the database performance that your application requires, and that you can scale up or scale down as your needs change.
RDS storage can be standard or Provisioned IOPS. You can choose the latter storage type if low latency is a critical requirement for your application.
In the case of MySQL and Oracle, RDS lets you seamlessly increase the amount of storage associated with your RDS service. Unlike traditional database administration, where deploying additional storage to a database is an extended, complex operation fraught with anxiety, RDS makes the process pain-free.
RDS supports multi-instance deployments with a master/slave arrangement, increasing performance and system resiliency. The master and slave can be placed in separate AZs to further increase resilience. If a database instance crashes, Amazon automatically restarts a new RDS instance and any associated read replicas configured for the RDS instance.
Relational databases are what most of us are used to. They have been around since the 70s. Think of a traditional spreadsheet.
Relational Databases on AWS (OLTP):
SQL Server
Oracle
MySQL Server
PostgreSQL
Aurora
MariaDB
Non-Relational Database
NoSQL
Data Warehousing (OLAP)
Redshift
RDS has 2 key features:
Mult-AZ – For Disaster Recovery
Read Replicas – For Performance
Non Relational Databases are as follows:
Collection = Table
Document = Row
Key Value Pairs = Fields
You can have as many columns as you want for any given row in a non-relational database. In a relational database, you must maintain consistency across rows in a table.
Data Warehousing
Used for business intelligence. Tools like Cognos, Jaspersoft, SQL Server Reporting Services, Oracle Hyperion, SAP NetWeaver.
Used to pull in very large and complex data sets. Usually used by management to do queries on data (such as current performance vs targets etc)
Data Warehousing databases use different type of architecture both from a database perspective and infrastructure layer.
Amazon's Data Warehouse solution is called Redshift
ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases.
ElastiCache supports two open-source in-memory caching engines:
Memcached
Redis
Automated Backups will allow you to recover your database to any point in time within a "retention period". The retention period can be between one and 35 days. Automated Backups will take a full daily snapshot and will also store transaction logs throughout the day. When you do a recovery, AWS will first choose the most recent daily backup up, and then apply transaction logs relevant to that day. This allows you to do a point in time recovery down to a second, within the retention period.
Automated Backups are enabled by default. The backup data is stored in S3 and you get free storage space equal to the size of your database. So if you have an RDS instance of 10GB, you will get 10GB worth of storage.
Backups are taken within a defined window. During the backup window, storage I/O may be suspended while your data is being backed up and you may experience elevated latency.
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