Question 1

What's the difference between a column-family database and a relational (SQL) database?

Accepted Answer

Relational databases store data in fixed tables with rows and predefined columns, and they use joins to combine data across tables. Column-family databases (wide-column stores) organize data by row key and column families, and each row can have different columns (sparse, flexible schema). Instead of joins, you typically model data around how you will query it, often duplicating (denormalizing) data to keep reads fast at scale.

Question 2

When should I use a column-family (wide-column) database?

Accepted Answer

Use a column-family database when you need very high write throughput, horizontal scaling across many nodes, and low-latency access by a known key (for example: userId, deviceId, contentId) or time-series style access patterns. It’s a strong fit for event logging, IoT telemetry, clickstreams, messaging/activity feeds, and large user/profile datasets where attributes vary. Avoid it when you need complex ad-hoc queries, frequent multi-table joins, or strict relational constraints across many entities.

Question 3

How much does a column-family database cost?

Accepted Answer

Cost depends on whether you run it yourself or use a managed service, and on throughput, storage, and replication. Managed options typically charge for (1) read/write capacity or node/instance size, (2) stored data size, (3) network/egress, and (4) backups and multi-region replication. Self-managed Cassandra adds operational costs (engineering time, monitoring, upgrades) plus compute, storage, and networking. For accurate estimates, size around peak reads/writes, data retention, and replication factor (more replicas increase cost but improve availability).

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