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Terminology

454 terms, tools, patterns and metrics an architect is expected to use precisely. Each one gets a short explanation of what it is, and — where it matters — what it is commonly confused with. Search filters as you type; the column headers sort.

All areas454 Architecture Fundamentals16 Distributed Systems73 Data Architecture71 Cloud Architecture55 Networking13 API & Integration Architecture17 Reliability & Resilience16 Observability14 Performance & Capacity Engineering13 Security Architecture50 Cost Architecture & FinOps12 Business Architecture9 Architecture Communication8 Enterprise Architecture8 Legacy Modernization11 AI-Era Architecture15 Software Architecture & Engineering19 Architecture Patterns15 Architecture Decision-Making11 The Architect's Meta-Skills8
Kind Any concept166 practice107 pattern93 case-study26 tool26 protocol22 metric14

9 terms shown.

Term Kind Topic What it is
Backfill practice ETL & ELT Re-running a pipeline over historical periods to populate new data or correct a past error, and the operation that proves whether a pipeline is well designed.
Data Contract practice Data Governance An explicit, versioned, enforced agreement between a data producer and its consumers about schema, semantics, quality and change policy.
Data Lineage practice Data Governance A record of where each dataset came from, what transformed it, and what depends on it — traced at table and ideally column level.
Data Retention Policy practice Data Architecture A defined rule for how long each class of data is kept, where, and what happens at the end of it.
Denormalisation practice Data Architecture Deliberately duplicating data across records to make reads cheap, accepting the write-time cost of keeping copies in step.
Idempotent Pipeline practice ETL & ELT A pipeline whose task can be re-run for the same input window any number of times and produce the same result.
Indexing Strategy practice Data Architecture Choosing the set of indexes a table carries by working backwards from its actual queries, and accepting the write cost that each one adds.
Normalisation Normal Forms practice Relational Modelling Organising a schema so each fact is stored exactly once, removing the update anomalies that duplication creates.
Pipeline Orchestration practice ETL & ELT Coordinating the execution of data tasks by dependency rather than by clock, with retries, backfill and observability built in.