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⚙️Backend Dev

Backend engineering, APIs, and databases

284 bites

Test yourself: Top 30 easy Backend Dev interview questionsMultiple choice, with the correct answer and why it is correct on every question. Free, no sign-in.

Easy everything in Backend Dev, page 3

easy1 min read

Connection pools and the problem they solve

A pool reuses pre-opened connections so requests skip the expensive connect handshake; without one, every request pays setup latency and may overwhelm the database.

easy1 min read

Purpose of database drivers (JDBC/ODBC)

A driver translates a standard API into each database's wire protocol, so app code stays portable across vendors.

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Least privilege for database service accounts

Grant each account only the minimum rights its job needs; for an app service account, scope grants to specific tables and verbs, never use the superuser.

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Full, differential, and incremental backups

Full copies everything; differential copies all changes since the last full; incremental copies changes since the last backup of any type.

easy2 min read

What is sharding and why shard over vertical scaling?

Sharding splits one dataset across servers by a shard key so each holds a subset; you shard because vertical scaling hits hardware ceilings, gets costly, and remains a single point of failure.

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What is database replication and why use it?

Replication keeps copies of data on multiple servers; primary benefits are high availability through failover and improved read scalability by spreading reads.

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What is the difference between ETL and ELT?

ETL transforms before loading, on a separate engine; ELT loads raw then transforms inside a scalable warehouse. Choose ELT with cloud warehouses and large raw or schema-on-read data.

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What is a star schema?

A central fact table of measures and foreign keys surrounded by denormalized dimension tables of descriptive attributes, joined in one hop for fast, simple analytical queries.

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What is the difference between OLTP and OLAP?

OLTP handles many short read-write transactions on normalized current data; OLAP runs few large analytical scans over denormalized historical data.

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What is the CAP theorem?

Consistency, Availability, Partition tolerance; during a network partition you must choose between staying consistent or staying available.

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How do you choose between relational and NoSQL databases?

Relational gives schema, joins, and ACID for structured related data; document gives flexible schema and horizontal scale for varied or denormalized data.

easy2 min read

Joining a large table with a small one

With a tiny table the optimizer often picks a hash join, building a hash table on the small side in memory, then probing it once per row of the large table in a single pass.

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Why developers read query plans

The plan shows the operators the optimizer chose to run a query; developers read it to find why a query is slow; a common thing to look for is a full table scan where an index was expected.

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Stages of executing a SELECT query

Parse the SQL into a tree, bind and validate against the catalog, optimize into a physical plan, then execute the plan operators fetching data and returning rows.

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Purpose of the Write-Ahead Log

WAL records changes sequentially and is flushed to disk before commit; the rule is log first, then data pages may lag; on crash the database replays the log to recover committed work.

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What is a database page?

A page is a fixed-size block, often 8KB, holding multiple rows; databases read and write whole pages because disk and OS I/O are block-oriented, amortizing seek cost and matching the buffer pool unit.

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Clustered versus non-clustered indexes

A clustered index orders the table's actual rows, one per table; a non-clustered index is a separate structure pointing to rows.

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Composite index column order for multi-column filters

Create one index on (last_name, first_name); order matters because the index serves leftmost-prefix lookups.

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What a database index is and when it helps

An index is a sorted lookup structure avoiding full scans, helps selective WHERE/JOIN columns, but costs write overhead.

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Database deadlocks and how engines resolve them

Define a deadlock as mutual waiting on locks, name detection plus victim rollback, and prevention by consistent lock ordering.

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