Analytics & OLAP
ClickHouse, StarRocks, analytical databases and OLAP systems
15 canonical articles
StarRocks 4.1: Adaptive Tablets, Range Distribution, and the Upgrade Trade-Offs
StarRocks 4.1 makes tablet layout adaptive: Range distribution, automatic splitting at 10 GB, and 100 GB tablets. When to enable it, and what it costs.
ClickHouse Explained (2026): MergeTree, Distributed Engine & Real-Time OLAP
Build blazing-fast analytics with ClickHouse columnar database. Learn MergeTree engine, data modeling, query optimization, and cluster deployment strategies.
TimescaleDB Hypertables, Continuous Aggregates & Compression (2026 Production Guide)
Use TimescaleDB for time-series data in PostgreSQL. Covers hypertable creation, continuous aggregates with refresh policies, retention policies, and 10-20x compression.
StarRocks vs ClickHouse: Architecture, Table Models & When to Choose Each (2026)
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.
StarRocks Monitoring & Alerting: The Complete Production Guide
Complete guide to StarRocks monitoring with Prometheus and Grafana. Covers resource saturation, cluster health, and application availability alerts with PromQL expressions and runbooks.
Real-Time Analytics Pipeline: PostgreSQL to ClickHouse via CDC
Build a real-time analytics pipeline from PostgreSQL to ClickHouse using CDC — architecture, latency, and schema mapping
OLAP vs OLTP: Choosing the Right Database for Your Workload
Understand the differences between OLAP and OLTP systems — query patterns, storage engines, and when to use a hybrid approach
Data Lakehouse Architecture: Delta Lake, Apache Iceberg, and Apache Hudi
Compare Delta Lake, Apache Iceberg, and Apache Hudi — ACID transactions, time travel, and format interoperability
ClickHouse MergeTree Engine: Storage Architecture and Query Optimization
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 for Database Engineers: In-Process Analytics Without the Cluster
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 vs Self-Hosted: Total Cost of Ownership in 2025
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.
Elasticsearch 8 vs OpenSearch 2: Which Fork to Choose in 2025?
Two years after the Elastic license change, Elasticsearch and OpenSearch have diverged significantly. Both are mature forks but the right choice depends on your use case, vendor lock-in tolerance, and team expertise.
ClickHouse vs BigQuery: Analytical Database Comparison for 2026
A detailed comparison of ClickHouse and BigQuery for analytical workloads — MergeTree engine vs Capacitor storage, self-hosted vs serverless cost models, query latency, real-time ingestion, and when to choose each.
StarRocks as a Vector Database – Architecture, Scaling, and Best Practices
Use StarRocks for high-performance vector search with HNSW indexes. Learn real-time vector ingestion, hybrid queries combining vectors with analytics, and scaling strategies.
TiDB Explained: The Complete Guide to Distributed SQL and HTAP
Explore TiDB distributed SQL database for HTAP workloads. Learn TiKV/TiFlash architecture, MySQL compatibility, horizontal scaling, and deployment strategies.