Database Insights

Build blazing-fast analytics with ClickHouse columnar database. Learn MergeTree engine, data modeling, query optimization, and cluster deployment strategies.

StarRocks is an open-source MPP analytics database. This 2026 guide covers FE/BE/CN architecture, the four table models, vectorized execution, and when to choose StarRocks over ClickHouse.

Complete guide to StarRocks monitoring with Prometheus and Grafana. Covers resource saturation, cluster health, and application availability alerts with PromQL expressions and runbooks.

Build a real-time analytics pipeline from PostgreSQL to ClickHouse using CDC — architecture, latency, and schema mapping

Understand the differences between OLAP and OLTP systems — query patterns, storage engines, and when to use a hybrid approach

Compare Delta Lake, Apache Iceberg, and Apache Hudi — ACID transactions, time travel, and format interoperability

Use dbt to build modular SQL transformations — models, tests, documentation, and CI/CD for your data warehouse

Compare CDC, ETL, and ELT — latency, complexity, cost, and when each pattern fits your data pipeline needs

2025 was the year databases competed on operational simplicity. Serverless databases matured, pgvector merged vector search into PostgreSQL, and CDC became standard infrastructure. Here's what mattered and what's next.

ClickHouse MergeTree is why ClickHouse queries 1 billion rows in 0.3 seconds. Learn how parts, merges, and sparse indexes work, and how to choose the ORDER BY key, secondary indexes, and MergeTree variants.

DuckDB brings OLAP query performance to your Python process without a server or cluster. Learn how to query Parquet files, replace heavy ETL jobs, and run analytics directly against PostgreSQL.

ClickHouse Cloud is convenient but can cost 3-5x more than a well-tuned self-hosted cluster at scale. This breakdown shows exactly where the cost lines cross.