ParadeDB is a PostgreSQL extension that provides full-text search, vector search, and analytics directly within the database, eliminating the need for a separate search service. The core engine is `pg_search`, which implements a custom index access method (`paradedb`/`bm25`) using Tantivy for search indexing and DataFusion for analytic aggregations. It supports BM25 scoring, phrase/term/boolean queries, fuzzy matching, proximity search, hybrid search (combining full-text and vector), and a rich set of tokenizers (including jieba, ICU, Lindera, ngram). The extension integrates deeply with PostgreSQL's planner through custom scan nodes (BaseScan, AggregateScan, JoinScan, MPP) to push down search, aggregation, and join operations into the index. It also offers columnar storage via fast fields, parallel query execution, and WAL-level integration for crash safety. Architecturally, the system is a Rust library compiled as a shared library loaded by PostgreSQL, using the `pgrx` framework for FFI. Entry points include SQL functions for search (e.g., `paradedb.query`, `pdb.score`), DDL for index creation, and custom plan/exec hooks. Data flows: user SQL queries are intercepted by the planner, which decides whether to use a custom scan path; if so, Tantivy or DataFusion executes the search/aggregation/join, producing tuples that are optionally post-processed by PostgreSQL (e.g., heap fetches, visibility checks). The extension relies on external dependencies: Tantivy (forked for block storage), DataFusion (for aggregate execution), ICU (for Unicode tokenization), Lindera (for Japanese tokenization), and Apache Arrow (for columnar data exchange).
SeekStorm is a high-performance search engine library and multi-tenancy server implemented in Rust. It provides both lexical (BM25F with proximity) and vector (ANN with IVF clustering and scalar/Turbo quantization) search capabilities, supporting real-time indexing, faceted search, spelling correction, query auto-completion, highlighting, and hybrid result fusion via RRF. The architecture consists of a core library (`seekstorm`), a RESTful server (`seekstorm_server`) with embedded web UI, and a Rust client SDK (`seekstorm_client`). The server uses memory-mapped files for persistence, supports per-index configuration of tokenizers, stemmers, stop words, and compression, and enforces multi-tenant isolation via API keys with resource quotas. Search performance is enhanced with SIMD acceleration (AVX2/NEON) for posting list intersection, vector quantization, and distance computations. The codebase is well-tested with extensive integration and consistency tests, and follows an explicit commit model for durability.
Infinity is a high-performance AI-native vector database designed for LLM applications, offering hybrid search over dense embeddings, sparse embeddings, tensors, and full-text. Its architecture is a distributed C++ core with a modular planner/executor, multiple index types (HNSW, IVF, BMP, DiskANN, EMVB, PLAID, full-text), and a transaction system with WAL and checkpointing. The database exposes a SQL interface, a Thrift RPC API, an HTTP API, and native SDKs for Python, Go, and C++. It also includes a web GUI (Next.js) for administration. The codebase is heavily optimized with SIMD instructions, custom analyzers for multiple languages, and advanced query optimization (fast rough filters, result caching). While the repository is actively maintained with a comprehensive test suite and CI/CD pipeline, there is some technical drift from deprecated KNN implementations and disabled unit tests, and the reliance on C++20 modules may introduce compiler compatibility risks.