Database Insights

Use Kafka Connect source and sink connectors to stream data between databases, warehouses, and event systems

Apply DynamoDB advanced patterns — GSI overloading, sparse indexes, single-table design, and access pattern modeling

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

Design MongoDB sharded clusters — choose shard keys, manage chunk balancing, and avoid hot shards in production

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.

Compare database sharding strategies: hash sharding for even distribution, range sharding for locality, and directory-based for flexibility. When to shard and alternatives.

Use Redis Streams for event sourcing and message queues. Covers XADD, XREADGROUP, consumer groups, XAUTOCLAIM for stale messages, and Python producer/consumer examples.

An honest comparison of MongoDB and PostgreSQL in 2026 — document model vs relational model, JSONB as a document store, ACID transaction trade-offs, horizontal scaling, licensing, and migration paths.

TiDB's write path crosses multiple layers — SQL parser, planner, TiKV region leader, Raft log replication, and 2PC commit — before a transaction is durable. Here's a complete walkthrough.

Use Apache Flink CDC to capture MySQL and PostgreSQL changes — stateful processing, exactly-once semantics, and Kubernetes deployment

Compare vector database options for AI workloads — pgvector in PostgreSQL, Pinecone, Weaviate, and Qdrant

Compare CockroachDB, Google Spanner, and YugabyteDB — consistency models, PostgreSQL compatibility, and operational costs