r2rtf
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
A side-by-side editorial comparison of nodbi and spiro — release velocity, themes, recent moves, and the top alternatives to consider.
One document API over six databases, and every release is spent absorbing their JSON engines' churn
nodbi presents a single document-store interface — docdb_create, docdb_query, docdb_update — over SQLite, DuckDB, PostgreSQL, MongoDB, CouchDB and Elasticsearch. The engineering reality behind that abstraction is that each backend's JSON support keeps moving, and the releases show it: jsonb_tree adopted as RSQLite 2.4.4 exposes it, json_tree reworked for DuckDB 1.3.0, then avoided entirely for DuckDB listfields because it was too slow. The 0.11.0 release in late 2024 is the one that changed the contract, making docdb_query() return columns of a single consistent type.
Cardiopulmonary exercise test data in R, one metabolic cart vendor at a time.
spiro imports and processes cardiopulmonary exercise testing data in R, handling the file formats that metabolic carts from Cosmed, Cortex, Vyntus, and ZAN emit, then interpolating, smoothing, and summarizing them into comparable variables. The bulk of ongoing work is vendor format compatibility rather than analysis features — 0.2.4 fixed Cosmed imports failing in rare cases and Cortex imports on newer devices, and 0.2.2 added English-language Vyntus files after 0.1.2 added French ones. The analysis side, spiro_max(), spiro_smooth() and spiro_plot(), has been stable for some time.
nodbi presents a single document-store interface — docdb_create, docdb_query, docdb_update — over SQLite, DuckDB, PostgreSQL, MongoDB, CouchDB and Elasticsearch. The engineering reality behind that abstraction is that each backend's JSON support keeps moving, and the releases show it: jsonb_tree adopted as RSQLite 2.4.4 exposes it, json_tree reworked for DuckDB 1.3.0, then avoided entirely for DuckDB listfields because it was too slow. The 0.11.0 release in late 2024 is the one that changed the contract, making docdb_query() return columns of a single consistent type.
Two threads dominate. The first is performance, pursued backend by backend: fast direct NDJSON import moved from DuckDB-only to SQLite and PostgreSQL, query refactors chasing each DuckDB release, and the removal of expensive tree-walking where a cheaper path exists. The second is making results predictable — consistent column types, version checks on the database backend, clearer messages when a Postgres database does not exist yet or when column names contain the dots nodbi reserves for JSON paths.
Given that most recent releases are triggered by DuckDB and RSQLite version changes, the next one likely follows the same pattern — adopting a new JSON function or working around a slow one. The duplicate-_id handling added in 0.14.0 suggests NDJSON ingestion edge cases are the current active area.
spiro imports and processes cardiopulmonary exercise testing data in R, handling the file formats that metabolic carts from Cosmed, Cortex, Vyntus, and ZAN emit, then interpolating, smoothing, and summarizing them into comparable variables. The bulk of ongoing work is vendor format compatibility rather than analysis features — 0.2.4 fixed Cosmed imports failing in rare cases and Cortex imports on newer devices, and 0.2.2 added English-language Vyntus files after 0.1.2 added French ones. The analysis side, spiro_max(), spiro_smooth() and spiro_plot(), has been stable for some time.
This is a mature rOpenSci package whose remaining work is dictated by other people's file formats. Each device firmware revision, each regional language variant, and each ggplot2 release generates maintenance, and that is what fills the changelog. The API itself settled early, with the 0.1.0 rOpenSci review pass renaming the protocol helpers to the pt_* prefix and 0.2.0 replacing the confusingly named spiro_import() with spiro_raw().
Expect the pattern to continue: import fixes as vendor formats shift and periodic plotting updates tracking ggplot2, with no indication of new analysis capability.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either nodbi or spiro.
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing
The stubbing library added httr2 support, then spent a year cutting itself free of everything else
crul took mocking back from webmockr and made it a property of the client itself
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — ropensci — within Analytics. nodbi and spiro are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nodbi and spiro are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top nodbi alternatives in Analytics are ranked by recent ship velocity. Browse the "nodbi alternatives" section above for the current picks, or visit /alternatives/nodbi for the full list with editorial commentary on each.
Top spiro alternatives in Analytics are ranked by recent ship velocity. Browse the "spiro alternatives" section above for the current picks, or visit /alternatives/spiro for the full list with editorial commentary on each.