We were discussing the benefits of managed RDS instance:
The managed database instance types offer a range of CPU and memory selections. Moreover their storage is scaleable on demand. Automated backups have a retention period of 35 days and manual snapshots are stored in S3 for durability. An availability zone is a physically distinct independent infrastructure. Multiple availability zones each of which is a physically distinct independent infrastructure comes with database synchronization so they are better prepared for failures. Read replicas help offload read traffic. Entire database may be snapshot and copied across region for greater durability. Compute, Storage and IOPS are provisioned constitute the bill.
Performance is improved with offloading read traffic to replicas, putting a cache in front of the RDS and scaling up the storage or resizing the instances. CloudWatch alerts and DB Event notifications enabled databases to be monitored.
In short, RDS allows developers to focus on app optimization with schema design, query construction, query optimization while allowing all infrastructure and maintenance to be wrapped under managed services.
RDS alone may not scale in a distributed manner. Therefore software such as ScaleBase allows creation of a distributed relational database where database instances are scaled out. Single instance database can now be transformed into multiple-instance distributed relational database. The benefits from such distributed database include massive scale, instant deployment, keeping all RDS benefits from single-instance, automatic load balancing especially with lags from replicas and splitting of reads and writes, and finally increased ROI with no app code requirements.
Does multi-model cloud database instance lose fidelity and performance over dedicated relational database ?
The answer is probably no because a cloud scales horizontally and what the database server did to manage partition is what the cloud does too. A matrix of database servers as a distributed database model comes with the co-ordination activities. A cloud database seamlessly provides a big table. Can the service-level agreement of a big table match the service-level agreement of a distributed query on a sql server ? The answer is probably yes because the partitions of data and corresponding processing are now flattened.
Are developers encouraged to use cloud databases as their conventional development database which they move to production ? This answer is also probably yes and the technology that does not require a change of habit is more likely to get adopted and all the tenets of cloud scale processing only improves traditional processing. Moreover queries are standardized in language as opposed to writing custom map-reduce logic and maintaining a library of those as a distributable package for No-Sql users.
#codingexercise https://ideone.com/Ar5cOO
The managed database instance types offer a range of CPU and memory selections. Moreover their storage is scaleable on demand. Automated backups have a retention period of 35 days and manual snapshots are stored in S3 for durability. An availability zone is a physically distinct independent infrastructure. Multiple availability zones each of which is a physically distinct independent infrastructure comes with database synchronization so they are better prepared for failures. Read replicas help offload read traffic. Entire database may be snapshot and copied across region for greater durability. Compute, Storage and IOPS are provisioned constitute the bill.
Performance is improved with offloading read traffic to replicas, putting a cache in front of the RDS and scaling up the storage or resizing the instances. CloudWatch alerts and DB Event notifications enabled databases to be monitored.
In short, RDS allows developers to focus on app optimization with schema design, query construction, query optimization while allowing all infrastructure and maintenance to be wrapped under managed services.
RDS alone may not scale in a distributed manner. Therefore software such as ScaleBase allows creation of a distributed relational database where database instances are scaled out. Single instance database can now be transformed into multiple-instance distributed relational database. The benefits from such distributed database include massive scale, instant deployment, keeping all RDS benefits from single-instance, automatic load balancing especially with lags from replicas and splitting of reads and writes, and finally increased ROI with no app code requirements.
Does multi-model cloud database instance lose fidelity and performance over dedicated relational database ?
The answer is probably no because a cloud scales horizontally and what the database server did to manage partition is what the cloud does too. A matrix of database servers as a distributed database model comes with the co-ordination activities. A cloud database seamlessly provides a big table. Can the service-level agreement of a big table match the service-level agreement of a distributed query on a sql server ? The answer is probably yes because the partitions of data and corresponding processing are now flattened.
Are developers encouraged to use cloud databases as their conventional development database which they move to production ? This answer is also probably yes and the technology that does not require a change of habit is more likely to get adopted and all the tenets of cloud scale processing only improves traditional processing. Moreover queries are standardized in language as opposed to writing custom map-reduce logic and maintaining a library of those as a distributable package for No-Sql users.
#codingexercise https://ideone.com/Ar5cOO
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