[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-replication::en":3,"gloss-cluster-replication::en":20,"gloss-next-replication::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"replication","data-infra","Replication","Replication is the practice of maintaining synchronized copies of a database across multiple servers, so that data isn't a single point of failure and read traffic can be distributed across more than one machine. Where sharding splits data horizontally (different servers hold different subsets of rows), replication does the opposite — every replica holds a full copy of the same data, kept in sync with the primary (also called the \"leader\" or \"master\") server. Why it matters for AI\u002FSaaS builders: replication underpins two things every production SaaS needs — availability (if the primary database server fails, a replica can be promoted to take over, minimizing downtime) and read scaling (analytics queries, reporting dashboards, and AI features that read heavily from the database — like pulling context for RAG — can be pointed at read replicas instead of competing with the primary for resources that need to stay fast for transactional writes). How it works: the standard pattern is primary-replica (or leader-follower) replication — all writes go to the primary, which streams a log of changes (in Postgres, the write-ahead log\u002FWAL) to one or more replicas that apply those changes to stay in sync. Replication can be synchronous (the primary waits for a replica to confirm it received the write before acknowledging the write as complete — safer, but adds latency) or asynchronous (the primary acknowledges the write immediately and replicas catch up shortly after — faster, but introduces replication lag, a brief window where a replica's data is stale relative to the primary). Replication lag matters concretely in application design: a common bug is writing data, then immediately reading it back from a read replica before replication has caught up, and getting a stale or missing result — a classic \"read-your-own-writes\" consistency problem that AI features are especially prone to (e.g., a user uploads a document, the app tries to embed it by reading from a replica that hasn't received the new row yet). Managed database services (AWS RDS, Google Cloud SQL, Neon, PlanetScale) typically offer one-click read replica provisioning. Worked example: an AI reporting SaaS runs expensive nightly aggregation queries across all customer data to generate AI-written summary reports. Running those queries against the primary production database would compete with live user traffic and risk slowing down the app for everyone; instead, the reporting job is configured to query a dedicated read replica, isolating the heavy analytical load from the transactional workload that needs to stay fast for real users placing real requests.","Replication keeps synchronized copies of a database on multiple servers, improving read scalability, availability, and disaster recovery.",null,[11,14,17],{"slug":12,"name":13},"data-warehouse","Data Warehouse",{"slug":15,"name":16},"postgresql","PostgreSQL",{"slug":18,"name":19},"sharding","Sharding",[21,25,28,31,34,38,41,44,47,50,54,57],{"slug":22,"category":5,"name":23,"updated_at":24},"acid","ACID","2026-08-24T02:46:37+00:00",{"slug":26,"category":5,"name":27,"updated_at":24},"ann-search","ANN Search",{"slug":29,"category":5,"name":30,"updated_at":24},"backpressure","Backpressure",{"slug":32,"category":5,"name":33,"updated_at":24},"batch-processing","Batch Processing",{"slug":35,"category":5,"name":36,"updated_at":37},"bm25","BM25","2026-08-24T02:46:38+00:00",{"slug":39,"category":5,"name":40,"updated_at":24},"cache","Cache",{"slug":42,"category":5,"name":43,"updated_at":24},"cap-theorem","CAP Theorem",{"slug":45,"category":5,"name":46,"updated_at":24},"change-data-capture","Change Data Capture (CDC)",{"slug":48,"category":5,"name":49,"updated_at":24},"chroma","Chroma",{"slug":51,"category":5,"name":52,"updated_at":53},"chunk-overlap","Chunk Overlap","2026-08-24T03:30:02+00:00",{"slug":55,"category":5,"name":56,"updated_at":24},"columnar-storage","Columnar Storage",{"slug":58,"category":5,"name":59,"updated_at":24},"connection-pooling","Connection Pooling"]