Daemon HTTP Endpoints: The Wire Contract
A walk through the actual HTTP surface mongreldb-server exposes, from /sql and /txn to sessions, pagination cursors, and the /kit/* typed routes, and why plain HTTP was the right transport bet.
Mongreldb
28 posts filed under mongreldb.
28
Posts
Aug 2026
Latest
The Single-Binary Economics of a Database
MongrelDB ships as one compiled binary per platform and one shared library per ABI, with cluster and cloud integrations excluded at compile time, and that shape is an economic decision as much as an engineering one.
Constraints at Commit Time, Not at Row Time
MongrelDB evaluates unique, foreign-key, and CHECK constraints atomically at transaction commit instead of per statement, which changes what a batch import can promise and what it has to fear.
MongrelDB vs Couchbase Lite for Offline Edge Applications
A technical comparison of MongrelDB and Couchbase Lite for embedded documents, offline sync, edge vector search, transactions, analytics, and security.
MongrelDB vs MongoDB Atlas for Document and Vector Search
A technical comparison of MongrelDB and MongoDB Atlas for documents, transactions, vector and full-text search, hybrid retrieval, deployment, and encryption.
MongrelDB vs Qdrant for Vector and Hybrid Search
A technical comparison of MongrelDB and Qdrant for dense and sparse vectors, filtering, hybrid search, transactions, deployment, and local RAG.
MongrelDB vs PostgreSQL, pgvector, and ParadeDB
A technical comparison of MongrelDB with PostgreSQL, pgvector, and ParadeDB for transactions, hybrid search, analytics, deployment, and operations.
MongrelDB vs DuckDB for Embedded Analytics
A technical comparison of MongrelDB and DuckDB for embedded analytics, transactions, vector and full-text search, Arrow workflows, and mixed workloads.
MongrelDB vs Turso and libSQL for Local-First Data
A technical comparison of MongrelDB with Turso and libSQL for embedded replicas, SQLite compatibility, vector search, analytics, synchronization, and security.
MongrelDB vs ObjectBox for On-Device Data and AI
A technical comparison of MongrelDB and ObjectBox for embedded applications, on-device vector search, transactions, synchronization, analytics, and encryption.
MongrelDB vs LanceDB for Embedded AI Retrieval
A technical comparison of MongrelDB and LanceDB for embedded vector search, hybrid retrieval, columnar data, transactions, RAG, and local deployment.
MongrelDB vs SurrealDB: Embedded Hybrid Databases
A technical comparison of MongrelDB and SurrealDB across embedded deployment, data models, transactions, SQL, vector search, hybrid retrieval, and operations.
MongrelDB vs SQLite: Choosing an Embedded Database
A technical comparison of MongrelDB and SQLite for transactions, analytics, vector and text search, encryption, deployment, and local-first applications.
MongrelDB Architecture: From WAL to Hybrid Search
An end-to-end technical walkthrough of MongrelDB, from transaction validation, WAL durability, MVCC, and PAX columnar runs to DataFusion SQL and hybrid retrieval.
Native JSON Columns Without Giving Up Types
A JSON column in MongrelDB is a typed column that the engine validates at write time and queries from the inside, so the schema-versus-schemaless argument stops being a binary you have to pick a side of.
Type System Inside a Database: Int64, Decimal128, JSON, Array, Interval
A column type is not documentation, it is a promise the storage engine can spend, and MongrelDB's type system covers fixed-width integers, decimal128 money, five flavors of time, sortable UUIDs, native JSON, and typed arrays so the engine can plan bytes instead of guessing at strings.
Multi-Process File Locking for the Embedded Case
A pure embedded engine never has to think about other processes, but MongrelDB is also a server, so it takes an exclusive advisory lock at open, fails fast by default, waits politely when you ask it to, and pushes genuine multi-process access through the daemon instead of through the filesystem.
Argon2id Credentials at the Storage Layer
Most database auth lives in middleware, which means every code path that skips the middleware skips the auth. MongrelDB stores Argon2id-hashed users and roles in the catalog and can enforce permissions on every transaction at the storage layer itself.
CDC and Replication in an Embedded Database
MongrelDB reconstructs change events from its own WAL and streams committed records to follower copies, so an embedded database can participate in replication and change data capture without bolting on a separate toolchain.
Idempotency Keys at the Storage Layer
MongrelDB binds idempotency keys into the commit log itself, so a retried write is safe across process crashes and restarts, not just across network drops.
WAL Group Commit: Accepted Writes and Durable Commits
MongrelDB separates accepted writes from fsync-backed durable commits, batches WAL work with group commit, and flushes log-structured columnar runs later.
PHP 8.4 Features We Use (and PHP 8.5 Features We Now Use)
PHP 8.4 is the floor of the pure PHP client, and PHP 8.5, released in November 2025, is where the language gives us enough to stop writing workarounds for cURL and readonly cloning.
Embedded and Server Modes from One Database Engine
MongrelDB runs in-process or behind mongreldb-server, keeping one storage and query engine while changing ownership, authentication, serialization, and resource boundaries.
Encryption at Rest Without Paying the SQLite SEE Tax
SQLite SEE is the official paid reference for SQLite encryption. Here is MongrelDB's open-source AES-GCM design, key hierarchy, WAL coverage, and search tradeoff.
Why MongrelDB Uses a PGM Learned-Range Index
MongrelDB's PGM learned-range index uses an epsilon-bounded piecewise linear model to predict sorted-key positions, then verifies the bounded range exactly.
HNSW Inside an Embedded Vector Database
How an embedded vector database keeps HNSW candidates, operational rows, SQL filters, sparse retrieval, and exact reranking inside one Rust engine.
FM-Index Substring Search in a Transactional Database
MongrelDB uses a Burrows-Wheeler transform and wavelet-tree FM-index for exact substring candidates that combine with SQL, vectors, ranges, and equality filters.
35 Languages, Two Boundaries, One MongrelDB Engine
MongrelDB supports 35 languages through nine embedded native bindings and 26 language-native HTTP clients, with one engine contract under both boundaries.