Why Notepad++, klogg, and VS Code All Fail on 100MB+ Log Files

Cord Rehn · April 20, 2026 · 7 min read

siftrlog-analysisdevtoolsdebugging

The Problem Nobody Talks About

Every developer has been there: a production incident, a 200MB log file, and a tool that takes 45 seconds to open it — if it opens at all.

You paste the path into VS Code. The progress spinner runs. And runs. Eventually you either get the file, or you get an out-of-memory error, or the editor quietly freezes and you force-quit it. Even when the file does open, searching it takes seconds per query. Scrolling lags. The tool was not built for this.

This is the log viewer at scale problem, and it’s largely invisible because most engineers work around it with whatever tool is at hand rather than asking why it happens or whether there’s a better way.

Here’s why these tools fail, and why Siftr doesn’t.

Notepad++

Notepad++ is one of the most beloved text editors in the Windows ecosystem, for good reason. It’s fast, feature-rich, and handles enormous ranges of file types gracefully.

For log files, it breaks down at scale for one fundamental reason: it loads the entire file into RAM before rendering anything.

What Happens

Open a 200MB log file in Notepad++ and watch your RAM. You’ll see memory usage spike to 600MB–1GB+. This is because Notepad++ (and most traditional text editors) work with an in-memory text buffer. They need the whole document in memory to support features like search, cursor navigation, undo history, and line numbering.

For a 200MB file, that means:

30–90 seconds of load time on a typical development machine
600MB–1.2GB of RAM consumed for the duration
UI lag on scrolling and Ctrl+F search
Potential crash if available RAM is constrained

Once loaded, Ctrl+F searches are actually reasonably fast because the full text is in memory. But the load penalty is real, and on very large files (500MB+), Notepad++ may simply fail to open them.

The other problem: Notepad++ gives you no log-specific capabilities. You can search for text, but you get no level filtering, no time-range navigation, no error rate visualization. It’s treating your log file like a text document, not a structured data source.

VS Code

VS Code is the reigning all-purpose editor, and many developers default to opening logs in it because it’s already open.

VS Code has the same fundamental architecture problem as Notepad++ when it comes to large files: it loads significant file content into its editor buffer and struggles with files above a certain threshold. Microsoft even hard-codes a warning for files over 50MB, noting that the editor experience will be degraded.

For a 200MB file:

You’ll see the large file warning immediately
Search becomes slow — VS Code’s ripgrep-based search is fast for codebases but was not designed for sequential log analysis
The editor may struggle with syntax highlighting at scale
Memory usage increases substantially

VS Code does have one advantage: the integrated terminal where you can run PowerShell Select-String or grep commands. But that brings us to the next option.

Estimated RAM for 200MB log in VS Code: 400MB–800MB+ depending on features engaged.

PowerShell Select-String (and grep)

This is the technically correct workaround that every developer who’s been doing this long enough eventually reaches. PowerShell’s Select-String (and grep on Unix) reads the file sequentially without loading it entirely into RAM. It’s memory-efficient and it works.

Select-String -Path "app.log" -Pattern "ERROR" | Select-Object -First 100

What you get: Lines matching your pattern, in their raw form, in your terminal.

What you don’t get:

Any structure or context
Time-range filtering without writing more complex pipelines
Level filtering beyond what you can express in a regex
Error rate trends
Component health analysis
Any visualization at all

Select-String is a power tool for targeted queries. It’s not a log viewer. For incident analysis, it puts you one query per insight — you have to already know what you’re looking for to construct the right query. That works if you have a hypothesis. It doesn’t work well for open-ended “what happened here?” investigation.

klogg

klogg (and its predecessor glogg) is the tool you find after you’ve given up on the general-purpose editors. It was built specifically for log viewing, and it handles large files much better than Notepad++ or VS Code because it doesn’t load the full file into RAM.

klogg uses memory-mapped file access and only reads the portions of the file that are currently visible in the viewport. It’s genuinely fast on large files.

Where klogg is good:

Opening large files quickly
Basic regex filtering
Multiple views with different filters
Not crashing on 500MB files

Where klogg falls short:

No analysis features — it’s a viewer, not an analyzer. You can filter lines, but you can’t ask “what’s the error rate over time?”
No forensic capabilities — no automatic incident report, no component health view, no lifecycle event detection
No heatmap scrollbar — navigating a 200MB file by scrollbar is still imprecise
Weak log4net/structured log support compared to tools purpose-built for those formats

klogg is the best option in the “general purpose log viewer” category. But it’s a viewer. It doesn’t analyze.

Memory Usage Comparison

For a 200MB log file, estimated peak RAM usage across tools:

Tool	Architecture	Est. RAM (200MB file)	Open time	Analysis features
Notepad++	Full in-memory buffer	600MB–1.2GB	30–90s	None
VS Code	Partial buffer	400MB–800MB	15–45s (with warning)	None
PowerShell Select-String	Stream reads	~50MB (stream only)	Instant (per query)	Manual queries only
klogg	Memory-mapped	~80–150MB	2–5s	Filtering only
Siftr	Worker-thread indexed	~120–180MB	<4s index	Full (Forensic Report, heatmap, F8 nav)

What Siftr Does Differently

Siftr was built specifically for the large log file problem. Every architectural decision reflects this:

Worker-Thread Indexing

Siftr indexes the file in a background worker thread, reading in 1MB chunks. The UI is responsive while indexing proceeds. You don’t wait for a full-file parse before you can interact with the viewer.

Virtual Scrolling

The log list in Siftr uses virtual scrolling with a hard limit of never more than ~100 DOM nodes. Regardless of file size — 50MB, 500MB, 1GB — the renderer only works with the visible rows. This is why scrolling in Siftr is as smooth on a 500MB file as on a 5MB file.

Compare to klogg or Notepad++, where scrolling a 200MB file involves rendering thousands of lines.

Heatmap Scrollbar

Traditional scrollbars on large log files are useless for navigation. A scrollbar represents the full file — moving it by 1 pixel jumps you thousands of lines. You have no idea where the errors are.

Siftr’s heatmap scrollbar overlays error density on the scrollbar track. You can see where errors cluster, navigate directly to incident windows, and never manually scroll through thousands of info-level lines to find the problem.

Read-Only File Access

Siftr opens log files in read-only mode with no file lock. The application process that’s actively writing to the log can continue writing without interference. This matters in production debugging scenarios where you’re tailing a live log.

Forensic Report

No other log viewer in this category has anything like the Forensic Report. The automated 6-pass analysis — time segmentation, error spikes, message clustering, component health, lifecycle events, synthesis — is the capability that turns Siftr from a viewer into an analysis tool.

The Bottom Line

Notepad++, VS Code, and grep are tools you already have. For small log files, they’re fine. For files over 100MB, they create more work than they save.

klogg is a real tool for the problem, and it’s a good viewer. It doesn’t analyze.

Siftr is the only option in this space that combines fast large-file viewing with automated forensic analysis. If you regularly debug .NET applications, IIS deployments, or any system that generates substantial logs, it’s the tool to have.

Download Siftr at sg57.dev/siftr — free, open-source, Windows. 200MB in under 4 seconds.