L3 Reference Guide
Databases Bigtable vs DynamoDB vs Cassandra vs MongoDB: A NoSQL Decision Framework
A workload-first framework for choosing among four distributed databases without substituting product categories for engineering requirements.
Cassandra
Write path fundamentals, compaction strategy, tombstone observability.
38 posts
L2 Deep Dive
Databases Bigtable vs Cassandra: Similar Data Models, Different Operating Boundaries
A principal-engineer comparison of Bigtable and Cassandra across key design, consistency, compaction, repair, scaling, and failure ownership.
L2 Deep Dive
Databases DynamoDB vs Cassandra: Managed Service or Operational Control
A workload-first comparison of DynamoDB and Cassandra across partitioning, consistency, multi-region behavior, capacity, and operational ownership.
L1 Field Note
Databases Design an IoT Platform for 10 Million Devices: Bigtable vs DynamoDB vs Cassandra vs MongoDB
A requirements-first design for one million telemetry writes per second, including burst admission, retention math, partitioning, and database tradeoffs.
L1 Field Note
Databases Why Distributed NoSQL Databases Develop Hot Partitions
How skewed keys overload physical partitions across Bigtable, DynamoDB, Cassandra, and MongoDB, with evidence-driven remediation.
L1 Field Note
Databases The Hidden Cost of Secondary Access Patterns in NoSQL
A workload-based method for evaluating DynamoDB GSIs, MongoDB indexes, Cassandra SAI, and Bigtable materialized views without invented amplification constants.
L1 Field Note
Databases The 2 AM NoSQL Incident: Failure Modes Across Bigtable, DynamoDB, Cassandra and MongoDB
A safe, evidence-first incident runbook for throttling, replica loss, elections, hot ranges, retry storms, and recovery across four NoSQL engines.
L2 Deep Dive
Databases From Cassandra to Bigtable, DynamoDB or MongoDB: When Modernization Is Worth It
A correctness-first framework for upgrading Cassandra or migrating to a managed database through ordered change capture, idempotent apply, and evidence-based cutover.
L2 Deep Dive
Databases Top 10 Apache Cassandra Use Cases and Architectures
A deep dive into the top production workloads where Apache Cassandra's masterless architecture excels, from time-series IoT to real-time recommendation engines.
L1 Field Note
Databases Chaos Engineering for Cassandra: Surviving Data Center Outages with Chaos Monkey
How Netflix uses Chaos Monkey to continuously test Apache Cassandra resilience, and how automated remediation prevents node failures from becoming outages.
L1 Field Note
Databases Tuning Cassandra 5.0: Unified Compaction Strategy, SAI, and Trie Memtables
The three Cassandra 5.0 features that need deliberate tuning rather than default settings: UCS scaling parameters, SAI index build order, and Trie memtable memory sizing.
L1 Field Note
Databases Cassandra Driver Tuning: Token-Aware Routing, Connection Pooling, and Prepared Statements
The client-side tuning levers that determine Cassandra latency before a query ever reaches the coordinator: routing, connection pools, and statement preparation.
L1 Field Note
Databases Cassandra Cache Tuning: Row Cache, Key Cache, and Chunk Cache
Why Cassandra's row cache is usually the wrong lever, and how key cache and chunk cache actually cut read latency without the invalidation trap.
L2 Deep Dive
Databases Cassandra Write Path Fundamentals for Database Engineers
How Cassandra's commit log, Memtable, and SSTable pipeline works, why write amplification is the dominant operational cost, and how compaction strategy selection changes it.
L2 Deep Dive
Databases Cassandra 5.0 for Operators: What SAI, UCS, Trie Memtables, and JDK 17 Actually Change
A deep dive into the physical storage engine overhaul in Apache Cassandra 5.0, explaining how Unified Compaction Strategy (UCS) and Storage-Attached Indexing (SAI) redefine cluster operations.
L1 Field Note
Databases Cassandra Data Modeling Fundamentals: Design From Queries, Not Entities
Why Cassandra schemas must be designed backward from access patterns rather than forward from entities, and how partition keys, clustering columns, and denormalization actually behave in production.
L2 Deep Dive
Databases Why We Moved from DataStax Enterprise to Apache Cassandra
How the playbook executes a zero-downtime migration of 45 nodes from proprietary DataStax Enterprise (DSE) to 100% open-source Apache Cassandra.
L1 Field Note
Databases Using Cassandra Full Query Logs and LLMs for Performance Troubleshooting
How to combine Apache Cassandra's Full Query Logging (FQL) with a safe, sanitized LLM diagnostic pipeline to triage complex latency regressions.
L1 Field Note
Databases Multi-DC Cassandra: Consistency, Replication, and Surviving a Datacenter Failure
How to survive an AWS regional outage by mastering Apache Cassandra's multi-datacenter replication, LOCAL_QUORUM consistency, and Hinted Handoff.
L1 Field Note
Databases Cassandra Node Lifecycle Operations: Bootstrap, Replace, Decommission, and RemoveNode
Understanding the difference between Apache Cassandra node lifecycle commands to prevent token confusion and stranded data when EC2 instances fail.
L1 Field Note
Databases Upgrading a 90-Node Cassandra Cluster from 4.1 to 5.0
How to orchestrate a zero-downtime major version upgrade from Cassandra 4.1 to 5.0 across 90 nodes, decoupling the database binary upgrade from the Java 17 transition.
L1 Field Note
Databases Automating Cassandra Patch Upgrades Across Large Clusters
How to engineer a zero-downtime rolling patch upgrade pipeline for Apache Cassandra using Ansible, strict pre-flight gates, and safe connection draining.
L1 Field Note
Databases Cassandra Backup and Restore on EC2: Snapshots, Incrementals, and S3
How Apache Cassandra backup mechanics actually work on AWS, from atomic on-disk hardlinks to S3 archiving and zero-downtime disaster recovery.
L1 Field Note
Databases Repairing a 90-Node Cassandra Cluster Without Crushing Production
How to orchestrate Apache Cassandra anti-entropy repair across multiple AWS regions using Cassandra Reaper, sub-range division, and inter-DC streaming limits.
L1 Field Note
Databases Merkle Trees and Cassandra Repair: Full vs. Incremental Repair in Real Production
How Apache Cassandra's anti-entropy repair actually works under the hood, and why incremental repair causes disk fragmentation without a managed full repair strategy.
L1 Field Note
Databases Debugging Cassandra Write Latency: CommitLog, Memtables, Flushes, and Backpressure
Tracing Apache Cassandra's write path to identify how saturated commitlogs and undersized memtable flush queues trigger massive write latency and client timeouts.
L2 Deep Dive
Databases Debugging Cassandra Read Latency: From CQL to SSTables
A deep dive into the Apache Cassandra read path, explaining how Bloom Filters, Key Caches, and Speculative Retries dictate millisecond query performance.
L1 Field Note
Databases Cassandra Data Modeling Reviews: How We Stopped Application Teams Creating Hot Partitions
Why treating Apache Cassandra like a relational database creates massive, node-crashing hot partitions, and how to use data bucketing to fix it.
L1 Field Note
Databases The Cassandra Tombstone Incident: Why Deletes Can Destroy Read Latency
How Apache Cassandra handles deletes, the mechanics of tombstones, and why deleting data can counter-intuitively crash your database read path.
L1 Field Note
Databases Cassandra Compaction: When STCS, LCS, and TWCS Become Your Bottleneck
Understanding the physics of Apache Cassandra compaction strategies, write amplification vs. read amplification, and when to migrate tables to survive production load.
L1 Field Note
Databases Linux and EC2 OS Tuning for Cassandra
Why default Linux AMIs destroy Apache Cassandra performance, and how to tune Transparent Huge Pages, swappiness, and disk readahead for stateful databases.
L1 Field Note
Databases G1GC Tuning for Cassandra: What I Actually Look At
How to tune the Java 11 G1 Garbage Collector for Apache Cassandra 4.x, eliminating humongous allocations, evacuation failures, and stop-the-world pauses.
L2 Deep Dive
Databases My Cassandra Performance Troubleshooting Playbook
A deterministic, 7-step playbook for isolating Apache Cassandra latency spikes, distinguishing between coordinator drops, GC pauses, and disk I/O bottlenecks.
L2 Deep Dive
Databases Capacity Planning Cassandra: When Do You Add Nodes?
Why sizing an Apache Cassandra cluster based on CPU utilization is a trap, and how to calculate physical capacity based on disk headroom, IOPS, and compaction debt.
L1 Field Note
Databases Scaling Cassandra from 27 to 36 Nodes Without Taking Production Down
How to safely expand an Apache Cassandra cluster horizontally using zero-copy streaming, vnodes, and staged bootstrap limits.
L1 Field Note
Databases Running Apache Cassandra on EC2: The Production Architecture We Standardized On
How to design a multi-AZ Apache Cassandra topology on AWS EC2, mapping physical availability zones to logical racks, with dedicated storage for data and commitlogs.
L2 Deep Dive
Databases Cassandra Observability: Compaction, Tombstones, Repair, Latency, and Hot Partitions
Why generic server monitoring fails for Apache Cassandra, and how to track the true operational signals of a distributed masterless database.
L1 Field Note
Engineering Fundamentals B-tree vs LSM Tree: The Storage Engine Tradeoff
Why PostgreSQL and MySQL use B-trees while Cassandra and RocksDB use LSM trees — the read/write tradeoff that determines which storage engine fits your workload.