Aim
An experiment tracker grinding on storage performance — and quiet for over a year.
Comparison · Analytics
Glances vs Polars
A side-by-side editorial comparison of Glances and Polars — release velocity, themes, recent moves, and the top alternatives to consider.
Glances vs Polars: at a glance
What is Glances?
Every Glances release this year has carried CVE fixes — the monitoring tool is being audited in public.
Six releases since March, and all but one ship security patches. 4.5.2 alone corrected eight CVEs: CORS defaults allowing cross-origin credential theft, incomplete secrets redaction leaking password hashes and SNMP credentials through /api/v4/args, missing host validation leaving the REST API open to DNS rebinding, SQL injection in the DuckDB export, command injection through process names in action templates, and credential leakage via Zeroconf-spoofed browser autodiscovery. The pattern continues through 4.5.3, 4.5.4, 4.5.5 and 4.5.6, the last fixing a value-level bypass that leaked credentials embedded in URL config values. Alongside it, hardware coverage keeps widening — Intel and AMD GPUs, NVIDIA Jetson, Rockchip NPU and MPP, Raspberry Pi VideoCore.
What is Polars?
A deprecation sweep and hive-partition join rewrites, shipped on two trains at once.
Polars releases Python and Rust builds in lockstep, with each Rust tag naming the Python version its DSL matches. The recent work is concentrated in two places: query-plan performance — len() pushdown into concat and union inputs, pre-partitioning on hive-partitioned joins, split multiplexers scanning in-memory DataFrames — and cloud IO, where an adaptive HTTP rate-limiter and a global DNS cache landed. Correctness fixes reach into unsoundness in rayon block_on and undefined behaviour on empty chunks.
Glances vs Polars: editorial side-by-side
Glances
2.5ANALYTICS
Every Glances release this year has carried CVE fixes — the monitoring tool is being audited in public.
◆ Current state
Six releases since March, and all but one ship security patches. 4.5.2 alone corrected eight CVEs: CORS defaults allowing cross-origin credential theft, incomplete secrets redaction leaking password hashes and SNMP credentials through /api/v4/args, missing host validation leaving the REST API open to DNS rebinding, SQL injection in the DuckDB export, command injection through process names in action templates, and credential leakage via Zeroconf-spoofed browser autodiscovery. The pattern continues through 4.5.3, 4.5.4, 4.5.5 and 4.5.6, the last fixing a value-level bypass that leaked credentials embedded in URL config values. Alongside it, hardware coverage keeps widening — Intel and AMD GPUs, NVIDIA Jetson, Rockchip NPU and MPP, Raspberry Pi VideoCore.
◆ Where it's heading
This is what it looks like when a tool that grew up as a local terminal dashboard gets taken seriously as a network service. Nearly every advisory in the window comes from the same root assumption — that the REST API, XML-RPC server and autodiscovery browser are on a trusted network — and the fixes are systematically removing that assumption: authentication warnings on startup, host validation, tighter CORS, redaction that covers values as well as keys. The feature work continues in parallel and is almost entirely about reading more kinds of hardware.
◆ Prediction
The advisories have moved from transport-level exposure toward data-level leaks in specific endpoints, which suggests the remaining audit surface is the export backends and config serialisation rather than the servers themselves. Expect the next release to follow the same shape: hardware plugin additions plus another round of endpoint fixes.
Polars
5.0ANALYTICS
A deprecation sweep and hive-partition join rewrites, shipped on two trains at once.
◆ Current state
Polars releases Python and Rust builds in lockstep, with each Rust tag naming the Python version its DSL matches. The recent work is concentrated in two places: query-plan performance — len() pushdown into concat and union inputs, pre-partitioning on hive-partitioned joins, split multiplexers scanning in-memory DataFrames — and cloud IO, where an adaptive HTTP rate-limiter and a global DNS cache landed. Correctness fixes reach into unsoundness in rayon block_on and undefined behaviour on empty chunks.
◆ Where it's heading
The 1.43.0 release carried seven deprecations at once — numeric-to-categorical casts, casts from non-nested dtypes into lists, bitwise ops between integers and booleans, LazyFrame.profile, unnamed list.to_struct calls — and 1.43.2 added more. That density of deprecation in minor releases is how a project narrows its type semantics before a major. Alongside it, Iceberg and Delta support keeps taking fixes, which is where the lakehouse-format work is showing up.
◆ Prediction
Expect the deprecation cycle to keep tightening casting and categorical semantics, with performance work staying focused on hive-partitioned and cloud-hosted data where the query planner has the most left to exploit.
Alternatives to Glances and Polars
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 Glances or Polars.
Zipkin
Zipkin's last release was January 2025 — a dependency bump, and then nothing.
OpenObserve
One release turns a telemetry store into synthetics, workflows, and AI observability.
Chord
Chord rebuilt Copilot, renamed it, and let it start building the audiences it used to describe
Citus
Citus is in maintenance mode across four branches, with the feature work invisible from the feed.
Pinpoint
ServerMap rebuilt and application names finally long enough to describe a service.
See all Glances alternatives → · See all Polars alternatives →
Recent activity from Glances and Polars
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoPolarsRust 0.55.2 adds an adaptive HTTP rate-limiter for cloud IO
- 2d agoPolarsRust 0.55.1 rewrites joins on hive-partitioned data
- 6d agoGlancesCredential leak via URL values in /api/4/config
- 6d agoPolarsPython 1.43.2 deprecates Categorical-to-integer casts
- 11d agoPolarsPython 1.43.1 allows callback sinks on cloud targets
- 17d agoPolarsPython 1.43.0 lands seven deprecations in one release
- 1mo agoPolarsPython 1.42.1 samples multi-file parquet metadata resolution
- 1mo agoGlancesContainer API latency, ARM GPU monitoring, and an AMP command-execution fix
- 3mo agoGlancesRockchip MPP and NPU monitoring, plus three CVE corrections
- 4mo agoGlancesLXC/LXD support, ClickHouse export, and two CVE mitigations
- 4mo agoGlancesEight CVEs corrected in one release
- 5mo agoGlancesStability fixes, Intel GPU monitoring, and container health alerting
Frequently asked questions
What is the difference between Glances and Polars?
They serve adjacent needs but don't currently overlap on shipped themes. Polars is currently shipping more aggressively (velocity 5.0 vs 2.5), with 0 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 Glances better than Polars?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Polars is currently shipping more aggressively (velocity 5.0 vs 2.5), with 0 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 Glances?
Top Glances alternatives in Analytics are ranked by recent ship velocity. Browse the "Glances alternatives" section above for the current picks, or visit /alternatives/glances for the full list with editorial commentary on each.
What are the best alternatives to Polars?
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.