Engineering deep dives, product updates, and insights from the HeliosDB team.
v3.6.1 → v3.6.3 in one comparison. Window functions −25%, INSERT throughput −17 to −31%, CTE −13%. Time-travel index validated at 39 000× over linear scan. Four silently-red regression tests now green.
Read more →Stage-driven upgrades with shadow-execution validation, chaos rehearsal, and time-travel replay rollback. The wedge into the PG-12-EOL migration market.
Read more →Real WASM plugin runtime, signed-plugin distribution via OCI, time-travel replay, zero-downtime PG major-version upgrade orchestrator, built-in admin console. Largest release in the project's history.
Read more →Three transports, twelve auto-registered tools, streaming progress events, single-shot discovery. Claude Code, Cursor, Continue, Codex, and Aider connect to HeliosDB Nano with no glue server.
Read more →WITH CONTEXT Clause and Why RAG Belongs in SQLVector store + graph DB + entity linker + reranker collapse into one engine. Eight ingestion adapters (incl. Docling), centrality re-rank, semantic-Merkle invalidation. 62 ms mean on 10k-node fixture.
Read more →33 of 35 categories match or improve over v3.6.0. DELETE point −36% (1000× on a 10K-row table), IN subquery −47%, DISTINCT −45%, JOINs ~−29%. Full 35-category breakdown, three deep-dives, and open caveats.
Read more →A patch release focused on the request path: 28–37% faster pool checkout, 3.1× faster metrics reads, zero-allocation protocol parsing, and concurrent L1 cache hits.
Read more →CREATE EXTENSION hdb_code; CREATE AST INDEX ON src/. The AST is a table; symbols are rows. Time-travel + branch on every lsp_* call. Eight languages, runtime grammar registry, in-process embedder.
Part 3 of the BaaS series. Three callers, three needs: long-lived servers want wire protocol, serverless workers want REST, agents want MCP. Why HeliosDB exposes all three on the same engine and how to pick per caller.
Read more →Five weeks, eight minor versions, three new tracks. Code-Graph (CREATE EXTENSION hdb_code), Graph-RAG (WITH CONTEXT clause), native MCP server. In-process fastembed, Docling ingestion, Drizzle/Prisma/TypeORM compat.
Part 2 of the BaaS series. A hands-on build: provision, schema with VECTOR(1536), seed with embeddings, per-user scoped keys, branch for a feature, time-travel to debug, self-host with the same code. No SDK, no backend.
Read more →Part 1 of the BaaS series. SQL portability isn't database portability — drivers, pools, auth, and provisioning leak through. A RESTful BaaS moves the seam to the HTTP boundary. Bootstrap in one POST, deploy anywhere, scale stateless.
Read more →Our biggest release yet: 193 crates, 14 protocol adapters, quantum-inspired optimization, and GPU acceleration for the enterprise.
Read more →A deep dive into Product Quantization and how we achieved 384x compression on high-dimensional vectors without sacrificing recall.
Read more →How zero-cost copy-on-write branching at the storage layer changes the way teams develop, test, and deploy schema changes.
Read more →Memory safety without garbage collection, fearless concurrency, and zero-cost abstractions. Here's why Rust was the only choice.
Read more →Fair, reproducible benchmarks comparing HeliosDB against PostgreSQL across OLTP, OLAP, and vector workloads on identical hardware.
Read more →A step-by-step guide to building Retrieval-Augmented Generation pipelines using HeliosDB's native vector search and SQL.
Read more →Our flagship connection router with multi-tier caching, GraphQL gateway, WASM plugins, and intelligent query routing.
Read more →How HeliosDB implements client-side encryption where even the database server cannot read your data. Security without compromise.
Read more →Real-world patterns for using AS OF queries in production: audit compliance, debugging, data recovery, and A/B testing analysis.
Read more →Row-Level Security, per-tenant resource quotas, and isolation patterns for building SaaS applications on HeliosDB.
Read more →Deploy a full-featured database at the edge: IoT sensors, mobile apps, and offline-first architectures with a ~50MB binary.
Read more →Why vector search is just the beginning. Our vision for databases that understand, predict, and adapt to your application needs.
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