PostHog
PostHog is filling in Logs and the mobile SDKs while quietly growing a support product.
A side-by-side editorial comparison of Polars and Holistics — release velocity, themes, recent moves, and the top alternatives to consider.
Polars is teaching its engine to spill, stream, and read the lakehouse.
Polars ships on two trains: the Python package, now at 1.43.2, and the Rust crate at 0.55.1 whose DSL is pinned to a matching Python version. Recent work concentrates in three places — the streaming engine, stabilized in the Rust 0.54.4 release and given out-of-core spilling in Python 1.42.0; the query optimizer, with predicate canonicalization, contradictory-filter elimination and nested common subplan elimination; and lakehouse table formats, where Iceberg, Delta and hive-partitioned layouts get dedicated join rewrites and scan parallelism. A steady deprecation wave runs alongside, mostly narrowing which casts the Categorical and Enum types permit.
Holistics keeps converting GUI-only BI objects into code, one class at a time.
The recent window moved custom charts into AML so they can be defined as code, built through a GUI and previewed against real data, and gave every file — dashboards, models, datasets — its own version timeline with per-file restore that does not revert anyone else's work. Smaller quality-of-life work landed alongside: theme-level color palettes, date-range presets and typed shorthands, chart suggestions in Explore, and custom currency and unit formats.
Polars ships on two trains: the Python package, now at 1.43.2, and the Rust crate at 0.55.1 whose DSL is pinned to a matching Python version. Recent work concentrates in three places — the streaming engine, stabilized in the Rust 0.54.4 release and given out-of-core spilling in Python 1.42.0; the query optimizer, with predicate canonicalization, contradictory-filter elimination and nested common subplan elimination; and lakehouse table formats, where Iceberg, Delta and hive-partitioned layouts get dedicated join rewrites and scan parallelism. A steady deprecation wave runs alongside, mostly narrowing which casts the Categorical and Enum types permit.
The engine work is pushing Polars past the fits-in-memory, single-machine dataframe it became known for. Spilling and a stabilized streaming engine chip at the memory ceiling; the cloud IO changes — global DNS cache, bytes-based concurrency control, non-blocking path expansion — target remote object storage rather than local files; and the hive, Iceberg and Delta join rewrites only pay off when reading a partitioned lake. The deprecations run the opposite direction, tightening a type system that had been permissive about casts.
The accumulating deprecations around categorical casts, list casts and integer-boolean bitwise ops, several already emitting FutureWarnings, point toward a breaking major release that removes them. On the engine side, the explicitly naive out-of-core spilling is the obvious next thing to be reworked.
The recent window moved custom charts into AML so they can be defined as code, built through a GUI and previewed against real data, and gave every file — dashboards, models, datasets — its own version timeline with per-file restore that does not revert anyone else's work. Smaller quality-of-life work landed alongside: theme-level color palettes, date-range presets and typed shorthands, chart suggestions in Explore, and custom currency and unit formats.
Holistics is steadily giving GUI concepts an AML representation while keeping a visual path to the same result, and file history extends a software-engineering model to objects that were previously edited in place. The last several releases are polish on top of that spine rather than new capability, which suggests the code-first migration sets the agenda and the surface work fills in behind it.
Expect more object types to gain AML definitions and version timelines; the cadence so far has been roughly one object class per release cycle.
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 Polars or Holistics.
PostHog is filling in Logs and the mobile SDKs while quietly growing a support product.
Mixpanel is becoming a component other tools provision, not a destination users visit.
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
With Interfaces, NocoDB stops being a database view and starts being an app builder.
Neo4j is making the graph legible to agents and comfortable for humans at the same time.
Looker's release feed is mostly page furniture; the shipping behind it is thin.
See all Polars alternatives → · See all Holistics alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Polars and Holistics are shipping at a similar cadence (velocity 5.0 vs 5.0, 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. Polars and Holistics are shipping at a similar cadence (velocity 5.0 vs 5.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top Polars alternatives in Analytics are ranked by recent ship velocity. Browse the "Polars alternatives" section above for the current picks, or visit /alternatives/polars for the full list with editorial commentary on each.
Top Holistics alternatives in Analytics are ranked by recent ship velocity. Browse the "Holistics alternatives" section above for the current picks, or visit /alternatives/holistics for the full list with editorial commentary on each.