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Notes: Designing Data-Intensive Applications

Notes: Designing Data-Intensive Applications. GitHub Gist: instantly share code, notes, and snippets.

Martin kleppmannNetwork dbsDesigning data intensiveData modelsOnline transaction processingOnline analytics processingStructured merge treesSorted string tablesBloom filtersLevenshtien automatonClustered indexCheap fileCovering indexConcatenated indexData cubesOriented architecture

Jepsen: RavenDB 6 0 2

Jepsen: RavenDB 6 0 2
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Taber bainKelly shortridgeSilvia botrosNathan taylorLeif walshZach tellmanRiak cassandraBen linsayC scott andreasAyende rahienIrene kannyoOren einiRead committedStrong serializabilitySnapshot isolationLast write wins

CockroachDB 23 2 Enhances Enterprise Architectures with Improved Postgres Compatibility and Built-in Resilience

CockroachDB 23 2 Enhances Enterprise Architectures with Improved Postgres Compatibility and Built-in Resilience
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Ramke ramakrishnanHenry cookXingyu guAaron rosenbaumNate stewartRick greenwaldAdam ronthalGartner incProduct office at cockroach labsLive migration serviceLandmark groupStored proceduresMigration servicePhysical cluster replicationRead committedAnnual outage analysis

Does Your Test Suite Account For Weak Transaction Isolation?

Does Your Test Suite Account For Weak Transaction Isolation?
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PostgreSQL Internals: 3 Things to Know About UPDATE Statements

I recently finished reading PostgreSQL 14 Internals by Egor Rogov. It is one of the great books that teach applied computer science without watering down the difficult parts. One particularly interesting topic is PostgreSQL’s execution of UPDATE statements. Updates in relational databases are inherently complex. They can be affected by conflicts, anomalies, and deadlocks. However, some behavior is specific to PostgreSQL. This can lead to surprises. 1. Write Amplification PostgreSQL generally does not update rows in-place.

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