Platform · 2010–now · Cloud Scale
Elasticsearch
Full-text search and log analytics at scale. Powerful, hungry, and everywhere in observability stacks.
Why Elasticsearch stuck
Elasticsearch stuck because grep does not scale and product search is revenue-critical. Cluster tuning is a career; that complexity is the moat. It fails when teams index everything without retention discipline.
Case studies
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Related
Practice · 2009–2019
NoSQL for Everything
Schema-optional databases sold as a lifestyle. Right tool for some jobs; default for none.
$ Startups ditched Postgres for document stores "because scale," then rebuilt relational integrity in application code — and paid twice when joins came back as a product requirement.
Platform · 2006–2018
Hadoop Everywhere
MapReduce as lifestyle. The elephant in rooms that needed a spreadsheet.
$ Enterprises stood up Hadoop clusters for gigabytes of data that fit on one Postgres instance. Hadoop admins, ZooKeeper nightmares, and ETL rewrites burned millions before Spark and cloud warehouses retired the elephant.
Platform · 2009–now
MongoDB
Document DB that became a punchline, then a grown-up product. Survived by getting serious about transactions and ops.