tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of nodbi and webmockr — 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.
The stubbing library added httr2 support, then spent a year cutting itself free of everything else
webmockr intercepts HTTP requests in R tests and returns stubbed responses, and since 1.0.0 it covers all three clients that matter — httr, httr2 and crul. The releases through 2025 have been about shedding dependencies: internal R6 classes unexported in 2.1.0, crul demoted from Imports to Suggests in the same release, and the mutual dependency with vcr severed in 2.2.0. The package now installs and runs without pulling in the rest of the rOpenSci HTTP stack.
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.
webmockr intercepts HTTP requests in R tests and returns stubbed responses, and since 1.0.0 it covers all three clients that matter — httr, httr2 and crul. The releases through 2025 have been about shedding dependencies: internal R6 classes unexported in 2.1.0, crul demoted from Imports to Suggests in the same release, and the mutual dependency with vcr severed in 2.2.0. The package now installs and runs without pulling in the rest of the rOpenSci HTTP stack.
Two arcs run in sequence. The first is coverage — multiple queued responses in 0.7.0, basic auth mocking, async through crul, then httr2 — building out what can be stubbed. The second, starting with 2.0.0, is correctness and independence: stubs are now deleted if an error occurs mid-construction rather than lingering half-built, partial matching arrives for bodies and queries, and the dependency graph is pruned release by release. The 2.2.0 split from vcr landed within a minute of crul's release taking mocking control into its own clients.
RequestPattern is documented as still exported in 2.1.0 but slated for removal, so the next major release is where that lands. Expect continued dependency pruning rather than new client support — the three clients that exist are already covered.
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 webmockr.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all nodbi alternatives → · See all webmockr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — ropensci — within Analytics. nodbi and webmockr 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 webmockr 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 webmockr alternatives in Analytics are ranked by recent ship velocity. Browse the "webmockr alternatives" section above for the current picks, or visit /alternatives/webmockr for the full list with editorial commentary on each.