engineering — RedDB blog

Jun 2026 Operations · 09 · 4 min RedDB on a Raspberry Pi: the smallest sane install A weekend exercise — image a Pi 5, install RedDB, load a hundred thousand rows, and see what happens when document + vector + KV + blob all live on a $80 board under the desk.
May 2026 Agents · 17 · 8 min Agent SDK on RedDB: building custom agents with native persistence A walk through the four surfaces of a small Agent SDK — tool registry, memory adapter, conversation log, eval hooks — backed by RedDB instead of a stack of services. Ends with a working code-review bot in under 300 lines that remembers what it has reviewed, per repository.
Engineering · 17 · 11 min Chunking inside the engine: when the DB owns segmentation Most RAG stacks chunk in Python glue between Postgres and a vector store. The result is a second pipeline that drifts. This post walks through what it looks like when chunking is a declarative rule attached to a column, reranking is a query operator, and the engine — not the application — owns segmentation.
Engineering · 17 · 8 min Hybrid search done right: lexical, vector, and filter in one plan A walk through the RedDB query planner fusing BM25, vector similarity, and a structured filter into a single execution plan — with EXPLAIN output, the cost model behind it, and what happens on the edge cases that trip up naive two-stage rerankers.
Engineering · 17 · 14 min One WAL, four data models: how cross-modality transactions actually work A deep dive into the shared write-ahead log that lets a document update, a vector insert, a KV write, and a blob commit land in the same transaction. Record layout, the fsync contention tradeoff, and the four mitigations we shipped before the tail latency became someone else's incident.
Migration · 17 · 9 min Postgres + pgvector → RedDB: a migration playbook with wall-clock numbers A step-by-step playbook for moving a production Postgres + pgvector workload to RedDB — dual-write, embedding backfill, query translation, cutover, rollback — with measured timings from a 12M-row test corpus and the three places teams trip over.
Engineering · 16 · 1 min Hello from inside the engine A first note on what we're building and why a multi-model engine matters in 2026.
Engineering · 16 · 10 min Stop stitching Postgres, pgvector, S3, and Redis Every modern app you ship is four databases in a trenchcoat. Here is the bill — in failure surfaces, ops playbooks, and consistency models — that nobody costs out before signing.
Engineering · 14 · 7 min The tradeoffs we made to fit four engines in one Document, vector, KV and blob in the same transaction is not free. Here's the per-modality tuning surface we cut, the plugin story we sacrificed, and the cold-blob latency tail we accepted.
RAG · 12 · 8 min RAG without a second database When your vectors live on the same row as the document they describe, the entire CDC-and-backfill layer of a RAG pipeline disappears — and a class of stale-retrieval bugs goes with it.
Field reports · 06 · 7 min Notes from compaction hell Three months of LSM compaction tuning at production scale — the latency tail we measured, the four configuration changes that actually moved P99, and the one we wish we'd made on day one.
Migration · 04 · 9 min When NOT to migrate: a checklist The companion piece to every migration post. A decision tree for staying on your current stack — team size, pain quantification, runway — so you do not pay migration tax for a problem you did not have.
Field reports · 02 · 6 min Snapshot isolation, in practice What snapshot isolation gives you, what it doesn't, the write-skew anomaly that still bites, and the one application pattern that fixes most real cases.
Apr 2026 Migration · 30 · 6 min MongoDB → RedDB: the queries that change shape Idiomatic translations from MongoDB to RedDB for the patterns that actually appear in production code — aggregation pipelines, change streams, GridFS, and the three places where the literal translation is wrong.
Operations · 29 · 9 min Disaster recovery for RedDB: PITR, snapshots, regional failover An operator playbook for RedDB disaster recovery — point-in-time restore with example commands, snapshot scheduling, cross-region replication topology, the RPO/RTO numbers you can actually hit, and an honest list of what we don't yet do.
Migration · 28 · 8 min Out of Firebase, into a real backend A migration playbook for teams that outgrew Firebase — auth bridge, Firestore doc model, security rules, real-time — and an honest look at what you lose when the magic console goes away.
RAG · 27 · 6 min The drift window: why your RAG retrieves stale chunks A customer-visible failure mode unique to two-store RAG — source updates, queue lag, retrievals against the old embedding. Anatomy of one outage and how same-transaction writes eliminate the window.
RAG · 26 · 7 min Building an agent memory layer on RedDB A copy-pasteable schema for episodic, semantic, and procedural memory in a single database — with the queries that retrieve them and the bookkeeping that keeps them honest.
Operations · 25 · 7 min Self-hosting RedDB: the real-world checklist An operator-grade checklist for running RedDB on your own infrastructure — container images, k8s manifests, volume sizing, monitoring, backups, network policies, and the secrets-management decisions that bite later.
Engineering · 24 · 9 min Why 'best of breed' loses at small scale The ops cost of running four engines instead of one, measured in person-hours at team sizes of 2, 5, and 15 engineers. Multi-model isn't only a scale concern — it's a small-team unlock.
Engineering · 22 · 9 min When you don't need RedDB An honest list of workloads where Postgres + pgvector, SQLite, or a single-purpose store will serve you better than RedDB. If your shape is on this list, save yourself the migration.

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