Database Insights

Compare ScyllaDB and Apache Cassandra — throughput, latency, operational complexity, and when to switch

Choose the right Cassandra compaction strategy for your workload — STCS for write-heavy, LCS for read-heavy, TWCS for time-series

Model data in Cassandra around query patterns — partition key design, clustering columns, and anti-patterns to avoid

Design Cassandra tables for time-series data that scale to billions of rows. Learn partition key design, clustering columns, TTL tombstone management, and bucket strategies.

Choose the right Cassandra compaction strategy: STCS for write-heavy workloads, LCS for read-heavy point lookups, and TWCS for time-series data with TTL-based expiry.

ScyllaDB 6.0's shard-per-core architecture delivers 3-8x Cassandra throughput on identical hardware. Learn the performance differences, migration path from Cassandra, and when ScyllaDB tablets beat vnodes.

Design Cassandra tables around query patterns, not entities. Covers partition key cardinality, hot partition prevention, time bucketing, and secondary indexes vs materialized views.

Master Apache Cassandra for planet-scale, always-on applications. Learn ring architecture, consistency levels, data modeling, compaction strategies, and multi-datacenter replication.