--- title: "Why Coinbase and Pinterest Chose StarRocks: Lakehouse-Native Design and Fast Joins at Terabyte Scale" url: https://daily.dev/posts/why-coinbase-and-pinterest-chose-starrocks-lakehouse-native-design-and-fast-joins-at-terabyte-scale-vuslm8vpb source_url: https://www.ssp.sh/blog/starrocks-lakehouse-native-joins type: article source: "Data Engineering Blog" published: 2026-08-06T13:39:35.106Z updated: 2026-08-06T13:40:04.003Z tags: ["data-engineering", "apache-iceberg", "olap"] reading_time: 29 upvotes: 2 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Why Coinbase and Pinterest Chose StarRocks: Lakehouse-Native Design and Fast Joins at Terabyte Scale **[Data Engineering Blog](https://daily.dev/sources/ssp)** · 29 min read · 2 upvotes · 0 comments ## Summary StarRocks is gaining traction among data engineers at companies like Coinbase, Pinterest, and Fresha as a high-performance OLAP engine capable of sub-second analytics on terabyte-scale data. The core differentiator over ClickHouse, Druid, and Pinot is native support for fast distributed joins via colocated join groups — tables sharing the same bucketing key, bucket count, and replica placement so joins happen locally without network shuffle. Coinbase uses StarRocks for crypto trade data with a hybrid hot/cold architecture: recent data in StarRocks native format on S3, cold historical data federated from Iceberg. Pinterest migrated from Druid and cut p90 query latency by 50% while using only 32% of prior infrastructure. Fresha achieved sub-100ms p95 web analytics queries. Key architectural decisions enabling this performance include a cost-based optimizer (CBO), delete-and-insert primary key updates, multi-tier caching (memory → local disk → S3), intelligent materialized views, and SIMD vectorized execution. Tradeoffs include a smaller community than ClickHouse, the need for careful upfront data modeling around partition and colocation keys, and occasional stability issues in new releases. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#data-engineering](https://daily.dev/tags/data-engineering), [#apache-iceberg](https://daily.dev/tags/apache-iceberg), [#olap](https://daily.dev/tags/olap) [View this post on daily.dev](https://daily.dev/posts/why-coinbase-and-pinterest-chose-starrocks-lakehouse-native-design-and-fast-joins-at-terabyte-scale-vuslm8vpb)