rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
dbplyr vs writexl
A side-by-side editorial comparison of dbplyr and writexl — release velocity, themes, recent moves, and the top alternatives to consider.
dbplyr vs writexl: at a glance
What is dbplyr?
dbplyr ends its two-year backend migration by dropping 1st edition support outright
dbplyr translates dplyr code into SQL, and 2.6.0 closes a migration that has been running since 2023: first-edition backends no longer work at all. The same release converts a long list of soft deprecations into hard failures and removes functions deprecated as far back as 2019. The releases before it were translation-quality work across SQL Server, Redshift, Snowflake, Postgres, Spark and Teradata.
What is writexl?
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
For most of its history writexl was a deliberately minimal wrapper: bump the vendored libxlsxwriter, handle NA and Date coercion correctly, support a list of data frames for multiple sheets, and nothing else. 2.0.0, released August 2026, changes that — near-full libxlsxwriter coverage, cell/worksheet/workbook formatting, cell comments, an `xl_cell_general` class carrying value, formula and hyperlink, a cell-by-cell refactor, libxlsxwriter 1.2.4, and memory-safety work. It landed the same day as 1.5.4, a typo fix on the old line.
dbplyr vs writexl: editorial side-by-side
dbplyr
0.0ANALYTICS
dbplyr ends its two-year backend migration by dropping 1st edition support outright
◆ Current state
dbplyr translates dplyr code into SQL, and 2.6.0 closes a migration that has been running since 2023: first-edition backends no longer work at all. The same release converts a long list of soft deprecations into hard failures and removes functions deprecated as far back as 2019. The releases before it were translation-quality work across SQL Server, Redshift, Snowflake, Postgres, Spark and Teradata.
◆ Where it's heading
The package is trading compatibility surface for a smaller, more consistent core it can actually evolve — qualified table names were overhauled in 2.5.0, sql() and ident() were refactored internally, and the cte argument gave way to a single sql_options() entry point. Backend breadth keeps growing at the translation level even as the extension API narrows.
◆ Prediction
With the edition split finally gone, expect the next cycle to spend its budget on dialect translations and the newer Spark/Databricks path rather than on further deprecation.
writexl
6.3ANALYTICS
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
◆ Current state
For most of its history writexl was a deliberately minimal wrapper: bump the vendored libxlsxwriter, handle NA and Date coercion correctly, support a list of data frames for multiple sheets, and nothing else. 2.0.0, released August 2026, changes that — near-full libxlsxwriter coverage, cell/worksheet/workbook formatting, cell comments, an `xl_cell_general` class carrying value, formula and hyperlink, a cell-by-cell refactor, libxlsxwriter 1.2.4, and memory-safety work. It landed the same day as 1.5.4, a typo fix on the old line.
◆ Where it's heading
The package has changed category. Its selling point was being the dependency-free, opinion-free way to get a data frame into xlsx; 2.0.0 makes it a formatting-capable writer that now compares itself against openxlsx2 in its own test suite. The cell-by-cell refactor is what made that possible and is also the largest structural change in the package's history. Note that a single contributor drove essentially all of it.
◆ Prediction
Expect follow-up releases fixing edge cases in the new formatting and comment APIs — the cell-by-cell rewrite is too large to land clean, and the 2.0.0 notes already mention an off-by-one in date columns.
Alternatives to dbplyr and writexl
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 dbplyr or writexl.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
taxize
taxize spends its releases absorbing other people's API changes, one dead source at a time.
See all dbplyr alternatives → · See all writexl alternatives →
Recent activity from dbplyr and writexl
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8d agowritexlwritexl 2.0.0 adds formatting, comments and full libxlsxwriter coverage ⚡
- 8d agowritexlwritexl 1.5.4 fixes a documentation typo
- 1mo agodbplyr1st edition backends removed; a wave of deprecations goes defunct ⚡
- 11mo agodbplyrDate and aggregate translation fixes across six SQL dialects
- 2y agodbplyrQualified table names overhauled; I() becomes the simple path
- 2y agodbplyrPreliminary Databricks Spark SQL backend; join fixes
- 2y agodbplyrdbplyr 2.3.4
- 3y agodbplyrdbplyr 2.3.3
- 5y agowritexlwritexl 1.4.0 updates libxlsxwriter to 1.0.3
- 6y agowritexlwritexl 1.2 fixes NA in formulas and hyperlinks
- 7y agowritexlwritexl 1.1 fixes NA strings and bit64 coercion
- 8y agowritexlwritexl 1.0 writes Date values as datetimes
Frequently asked questions
What is the difference between dbplyr and writexl?
They serve adjacent needs but don't currently overlap on shipped themes. writexl is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is dbplyr better than writexl?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. writexl is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to dbplyr?
Top dbplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dbplyr alternatives" section above for the current picks, or visit /alternatives/dbplyr for the full list with editorial commentary on each.
What are the best alternatives to writexl?
Top writexl alternatives in Analytics are ranked by recent ship velocity. Browse the "writexl alternatives" section above for the current picks, or visit /alternatives/writexl for the full list with editorial commentary on each.