Alternative databases

**Relational** (tables), **document** (varying fields), **key-value** (fetch by key), **graph** (nodes and edges), **column-family** (columns grouped).

When the **relationships are the question** — "friends of friends" is one traversal against a self-join per level in SQL.

**Query the value.** You fetch by key or not at all, which is why it suits caches and sessions.

**Joins** and enforced schema — so data is duplicated, and update anomalies return.

**No, a trade.** Relational remains right for most business data because it enforces structure and transactions.

**Analysing history** — few enormous reads — as opposed to an operational database recording many small transactions.

**Extract** from each source, **Transform** into one consistent shape, **Load** into the warehouse. Transform is where most of the work is.

So analytical queries **avoid joins**. It is safe because the warehouse is rebuilt in bulk and never edited, so update anomalies cannot arise.

Only as current as the **last load** — often nightly. It never answers "what is happening right now".

**No.** It holds **transformed** data, not the originals, so the business could not be restored from it.

**OLAP** answers a question you already have. **Data mining** finds patterns you did not ask about — one confirms, the other suggests.

**Drill down** to finer detail (year → quarter → month). **Roll up** to a coarser summary (store → region → country).

**Slice** fixes **one** dimension to a single value. **Dice** fixes **several** dimensions to ranges.

**Association** (occur together), **clustering** (groups), **classification** (predict a label), **anomaly detection** (unlike the rest).

Test enough combinations and some look significant **by chance**. It must be validated on data not used to find it — and it is never causation.

**Replication** keeps copies of the same data (availability, read speed). **Fragmentation** splits data between machines (capacity, writes).

**That portion becomes unavailable** — unless the shard is also replicated, which is why real systems do both.

During a network partition you either **refuse to answer** (consistent) or **answer from a reachable copy** (available, possibly stale). You cannot have both.

A bank chooses **consistency** — better to refuse than to allow a double withdrawal. A social feed chooses **availability** — a late post is harmless.

Copies are brought into step **shortly after** a write, not instantly — so a read straight after a write can return the old value.