Amazon RDS managed databases in Kolkata

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Amazon RDS managed databases

The database, without the part where somebody has to remember to run backups.

Managed database

Chosen per project

Maintainable handover

Running your own database server is entirely doable and almost never worth it. Patching, backup scheduling, failover and point-in-time recovery are all solved problems, and RDS solves them for a modest premium over the raw compute.

What it does not solve is schema design, indexing or query quality — and those are where most database performance problems actually come from. A managed instance makes a badly designed schema highly available, not fast.

What we build with Amazon RDS

Any production relational database that matters to the business

Applications needing point-in-time recovery after a bad data change

Multi-AZ deployments where a few minutes of downtime is costly

Read-heavy reporting served from a replica

Where it fits — and where it does not

Good fit when

Standard PostgreSQL, MySQL, MariaDB or SQL Server workloads

Teams without a dedicated database administrator

Anything where a tested restore path is a requirement

Consider something else when

Workloads needing OS-level database extensions RDS does not permit

Very small projects where a managed container database is cheaper

What managed buys

The work RDS takes off your desk

Each of these is a task somebody has to do on a self-managed database, every month, forever.

Patching

Engine updates applied in a maintenance window.

Backups

Automated, retained, restorable to a point in time.

Failover

Standby in another availability zone, promoted automatically.

Monitoring

Metrics and slow queries surfaced without extra tooling.

How we work with Amazon RDS

Private subnets only

The database is never reachable from the internet; applications connect from inside the VPC.

Backups and PITR

Automated backups with a retention window, and a documented point-in-time restore that has been rehearsed.

Right-sized, then reviewed

Instance class and storage chosen from measured load and revisited once real usage exists.

Slow query visibility

Performance Insights and slow query logging on, because indexing problems show up there first.

Our typical Amazon RDS setup

Typical Amazon RDS stack choices and what we use for each
ConcernWhat we use
EnginesPostgreSQL, MySQL, MariaDB, SQL Server
AvailabilityMulti-AZ standby where downtime has a cost
BackupsAutomated snapshots plus point-in-time recovery
NetworkingPrivate subnets, security-group-restricted access
ScalingVertical resize, plus read replicas for reporting load

Frequently asked questions

Usually with little or no application change, since the engines are standard. The work is in planning the cutover window and verifying the data afterwards, not in rewriting queries.

It roughly doubles the instance cost to remove most single-zone failure risk. For a system the business runs on, yes. For an internal tool that can be down for an hour, often not.

Only if the bottleneck was the hardware. More often it is a missing index or a query pattern, which we would look at first — that costs nothing per month.

Topics people search for

Services built with Amazon RDS

Tell us what you are trying to build

Describe the problem in plain language and we will tell you what it would take to solve it — the approach, the moving parts and the sensible order to build them in. No obligation either way.

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