Edgewonk vs. TradeJour: Which Trading Journal is Right for You? (2026)

Two serious trading journals. One built for depth. One built for speed. Here's how to figure out which one belongs in your workflow.

Edgewonk Has Earned Its Reputation

Let's be clear upfront: Edgewonk is one of the most respected trading journals in the industry. If you've spent any time in serious trading communities — Reddit, Discord servers, prop firm forums — you've almost certainly seen it recommended. That reputation is deserved.

But respected doesn't mean right for everyone.

If you're a backtesting trader who lives in TradingView — replaying charts, annotating setups, building an edge across hundreds of trades — you might be spending more time on data entry than on actual analysis. That's a friction problem. And friction is the number-one killer of journaling consistency.

Here's a scenario that probably sounds familiar:

1. You block off a Saturday morning for backtesting
2. You spend 4 hours in Bar Replay, working through 30+ setups
3. You annotate your charts, take your screenshots, note your observations
4. You open your journal to log the session — and the energy immediately drains out of you
5. "I'll do it properly tomorrow," you tell yourself
6. You don't

This isn't a discipline problem. It's a friction problem. When journaling requires more effort than the trading itself, consistency breaks down.

This comparison isn't about which tool is objectively "better." It's about which tool fits your specific workflow. By the end of this article, you'll have a clear answer.

Quick Comparison

Part 1: What Edgewonk Does Well

Edgewonk has been around since 2016. In trading software terms, that's ancient — and it shows in the polish and depth of the product.

Deep Analytics and Reporting

Edgewonk's analytics suite is genuinely impressive. You get detailed performance breakdowns across dozens of metrics: win rate by session, P&L by day of week, average R-multiple, trade duration analysis, drawdown curves, and more. Each metric is filterable by custom tags you define — so you can slice your data by setup type, market session, emotional state, or any other variable you track.

For traders who want to go deep on their data, Edgewonk provides the infrastructure to answer very specific questions:

• "Does my edge disappear on Fridays?"
• "Am I statistically worse when I enter after news events?"
• "Which setup type has the best expectancy over 200+ trades?"

Few tools offer this level of analytical richness. If you love data and want to mine your trading history for patterns, Edgewonk is hard to beat.

Customisable Journal Fields

Edgewonk lets you build out your journal to match exactly how you trade. Add custom fields for things specific to your strategy: setup type, market structure context, entry trigger, emotional rating before the trade, position sizing rationale. The system is flexible enough to adapt to virtually any trading methodology.

This customisation means Edgewonk can serve a scalper, a swing trader, a prop firm trader, and a long-term investor — each with a completely different field configuration.

Desktop App — Works Offline

Edgewonk is a desktop application, not a web app. For a significant segment of traders, that's a feature, not a limitation.

Your data lives locally on your machine. There's no server to go down, no internet dependency mid-session, and no concern about your performance data living on someone else's infrastructure. For privacy-conscious traders or those who work in environments with unreliable connectivity, the desktop-first model is a genuine advantage.

The app runs on both Windows and Mac, with a clean interface that's been refined over years of user feedback.

Mature Product with a Proven Track Record

When you're choosing a tool you'll rely on for years, maturity matters. Edgewonk has been battle-tested by thousands of traders, maintains an active user community, and has a long history of consistent updates. The documentation is thorough. YouTube tutorials are plentiful. If you run into a problem, someone has almost certainly already solved it and posted about it.

Nine years of iteration also means the edge cases are smoothed out. The import/export works reliably. The reports render correctly. The sync doesn't corrupt your data. These things sound boring until you've lost journal data — at which point they're everything.

Broker Import Integrations

For live traders, Edgewonk's broker import functionality is a clear differentiator. Connect your broker account (or import a CSV export) and Edgewonk pulls in your actual executed trades automatically — including entry price, exit price, position size, and P&L.

If you're managing live positions and want your journal current without manual entry after every trade, this is a meaningful workflow advantage. Your journal becomes a reflection of your actual trading activity, not a manually maintained record that's always slightly behind.

Part 2: Where Edgewonk Falls Short

Here's where we need to be honest about a structural limitation that significantly affects backtesting traders: Edgewonk does not extract data from your screenshots.

Every Backtest Trade Requires Manual Entry

When you backtest in TradingView using Bar Replay, here's what you're working with:

1. You step forward candle by candle, making real-time decisions
2. You identify a setup — mark your entry, stop, and target on the chart
3. You screenshot the annotated chart
4. You step forward to the outcome and screenshot the result

At the end of a session, you might have 30–50 screenshots representing 30–50 trades. All the data you need — pair name, direction, entry price, stop loss level, take profit level, the date — is right there in those images.

With Edgewonk, you then open the app and type all of it in. Every field. Every trade. By hand.

For a 40-trade session, that's easily 45–60 minutes of admin work after an already-demanding session. The trades are logged, technically — but the experience is grinding enough that many traders find themselves logging in batches, or skipping sessions entirely, or simplifying their entries to reduce the pain.

"The best analytics suite in the world is useless if journaling friction stops you from building the dataset in the first place."

This is the core trade-off. Edgewonk optimises for what you can do with your data. It doesn't optimise for making that data easy to enter.

Screenshot Storage ≠ Screenshot Analysis

To be fair, Edgewonk does let you attach screenshots to trades. But attaching a file is very different from reading it.

When you attach a screenshot to an Edgewonk trade, Edgewonk stores the image as a reference attachment — a file you can open later to look at your chart. It doesn't extract the pair name from the screenshot. It doesn't read the price levels. It doesn't pull the stop loss or take profit from the visible drawing tools. You still type all of that in manually.

For backtesting traders, this distinction is critical. The screenshot is your data source. Everything you need to log a trade is visible in the image. A tool that can store screenshots but not read them is only solving half the problem.

Desktop-Only: No Cloud Sync, No Mobile

Edgewonk's desktop architecture means your journal lives on one machine. If you backtest on a desktop but want to review your stats on a laptop while travelling, you need to manually export and transfer your database. There's no automatic sync.

Mobile access doesn't exist. If you want to review a specific trade on your phone between sessions, check your win rate on the go, or quickly log something from a tablet — you can't.

For traders who work across multiple devices, or who want to review their journal as part of a broader review process outside their main trading setup, this is a real constraint.

Price Point for Part-Time Traders

At €169/year, Edgewonk is a serious commitment. For full-time traders or funded prop firm traders, it's easily justifiable. For hobbyists, students, or traders still finding their feet, it's a significant ask — especially if they're not yet at the point where they'll use 20% of the feature set.

This doesn't make Edgewonk bad value for the right user. But price-to-feature fit matters. Paying €169/year for a journal you use at 30% capacity is a different calculation than paying for something you push to its limits.

The Configuration Overhead

Edgewonk rewards investment. Set it up well — with the right custom fields, tags, and reporting preferences — and it becomes a powerful system tailored to your strategy.

But getting there requires work. New users often report a meaningful learning curve: understanding how the tagging system interacts with reports, deciding which custom fields actually matter for their strategy, configuring the journal in a way that makes future analysis useful. The documentation helps, but it's still a barrier.

For traders who want to start logging trades today and build habits before worrying about optimisation, the upfront overhead of Edgewonk can delay momentum.

Part 3: What TradeJour Does Well

TradeJour was built to solve one specific problem: backtesting traders spend too much time on data entry and not enough time on analysis.

The product is designed around a single assumption — you take TradingView screenshots, and those screenshots contain all the data you need to log a trade. The entire workflow is oriented around making that data extraction automatic.

AI Screenshot Extraction — Zero Typing Required

Upload a TradingView screenshot to TradeJour and the AI extracts your trade data automatically. The currency pair, direction (long or short), entry price, stop loss level, and take profit target are parsed directly from the image using a combination of Google Cloud Vision OCR for text extraction and Claude Vision API for visual chart analysis.

The two sources are merged with confidence scoring — so if the OCR is uncertain about a price level, the visual analysis fills the gap, and vice versa. The result is a pre-populated trade entry that you review and confirm, rather than a blank form you fill from scratch.

For a 40-trade backtest session, your logging time drops from 45–60 minutes of manual entry to 5–10 minutes of reviewing AI extractions and confirming they're correct. Your role shifts from data clerk to data verifier.

That's not a marginal efficiency gain. Across a year of backtesting sessions, it represents tens of hours returned to analysis.

Multi-Screenshot Per Trade (HTF → LTF Workflow)

Most serious backtesting traders don't work from a single timeframe. A typical workflow looks like this:

1. Weekly/Daily chart: Identify the higher-timeframe bias and key levels
2. 4H/1H chart: Confirm trend structure and look for confluence
3. 15M/5M chart: Find the precise entry trigger

That's three screenshots representing one trade. Each one tells part of the story. Logging just the entry chart loses the higher-timeframe context — which is often where the reason for the trade lives.

TradeJour supports multi-screenshot uploads per trade, preserving the HTF→LTF context as a coherent record. When you review that trade six months later, you see the full story — the context that led to the decision, not just the entry candle.

Purpose-Built for TradingView Backtesting

TradeJour isn't a general-purpose journal trying to serve every possible trading style. It's specifically designed for traders who backtest using TradingView's annotation tools and Bar Replay feature.

That focus means less configuration required out of the box. The upload flow, verification step, and trade fields are all oriented around the way TradingView backtesting traders actually work. You're not adapting a general tool to your workflow; you're using one built for it.

Cloud-Based — Access From Anywhere

Your TradeJour journal lives in the cloud. Log a session on your desktop, review your analytics on a laptop later, pull up a specific trade on your phone. Your data is current and consistent across every device, without manual sync or export.

For traders who move between devices, review their journal away from their main setup, or share access with a trading partner or coach, cloud access is a meaningful practical benefit.

Faster Journaling Drives Higher Consistency

The most underrated benefit of reducing data entry friction isn't the time saved. It's the consistency gained.

Traders who log every trade — including the ugly ones, the revenge trades, the "I knew I shouldn't have taken that" trades — have better data than traders who log selectively. Complete data gives you honest analytics. Honest analytics reveal the actual patterns in your behaviour, not the flattering version.

A tool that makes logging easy enough to do immediately after every session, every time, builds a dataset that a tool requiring 60 minutes of manual entry per session simply won't. That dataset is worth more than any analytics feature.

Part 4: Where TradeJour Falls Short

Honest comparisons require honest limitations. Here's where TradeJour genuinely comes up short.

No Broker Import (Yet)

TradeJour currently does not support broker imports or CSV trade imports from live accounts. If you're a live trader who wants to automatically sync your real executed trades from your broker, TradeJour is not the right tool today.

The product is optimised for backtesting — uploaded screenshots, AI extraction, verification. Automated live data feeds are not yet supported. If this is a non-negotiable requirement for your workflow, Edgewonk wins this category clearly.

Fewer Analytics Than Edgewonk

TradeJour is a newer product. Edgewonk has had nearly a decade to build a comprehensive analytics suite; TradeJour's reporting is more limited by comparison. You get the core metrics — win rate, R-multiple, P&L over time, performance by pair — but you won't find the same depth of filtered analysis, custom charting, or detailed session-based breakdowns that Edgewonk offers.

If you're the kind of trader who lives in the analytics dashboard and wants to cut your data 15 different ways, Edgewonk's reporting infrastructure is more mature and more comprehensive right now.

Works Best With TradingView Screenshots

TradeJour's AI extraction is calibrated for TradingView's specific visual style — the chart layout, drawing tools, price labels, and annotation formatting. If you trade primarily on a different platform — MetaTrader, NinjaTrader, cTrader, or a broker's proprietary platform — extraction accuracy drops meaningfully.

The tool isn't completely unusable with non-TradingView screenshots, but it's not where it shines. If TradingView isn't your primary charting platform, you lose much of TradeJour's core advantage.

Requires an Internet Connection

As a cloud-based tool, TradeJour requires internet access to function. If you backtest in an environment with unreliable or no connectivity, or if you have strong preferences for fully offline data storage for security reasons, this is a genuine constraint.

Part 5: Which Should You Choose?

Here's the honest summary — two clear decision trees based on your actual workflow.

Choose Edgewonk if:

• You're already comfortable with manual data entry. If the typing hasn't stopped you from journaling consistently, Edgewonk's analytical depth rewards that discipline.
• You need broker import for live trading. If your primary use case is tracking live trades from your broker account automatically, Edgewonk's import integrations are a clear advantage.
• You prefer desktop-only, offline storage. Privacy-conscious traders or those working in low-connectivity environments will value Edgewonk's local data model.
• You want mature, deep analytics. If you plan to spend serious time in performance dashboards slicing your data by session, day, setup type, and emotional state, Edgewonk's analytics suite is genuinely excellent.
• Your trading platform isn't TradingView. If you're on MT4, MT5, or a broker's proprietary platform, Edgewonk's manual entry model works regardless of where your charts live.

Choose TradeJour if:

• You backtest primarily on TradingView. If Bar Replay and TradingView annotations are your core workflow, TradeJour is built specifically for this.
• Manual data entry is killing your consistency. If you finish sessions planning to "log them tomorrow" — and tomorrow rarely comes — friction is your real problem. TradeJour eliminates it.
• You take multi-timeframe screenshots. HTF→LTF context captured in a single trade record is something TradeJour handles natively.
• You want to start quickly without configuration overhead. Upload a screenshot and you're logging. The learning curve is minimal.
• You work across multiple devices. Cloud access means your journal is always current wherever you are.

"The best trading journal isn't the one with the most features. It's the one you'll actually use consistently enough to build real data."

Conclusion

Edgewonk and TradeJour are both serious tools built for serious traders. They solve the same core problem — building a consistent, data-rich journal — but from opposite directions.

Edgewonk is a depth-first tool: mature, analytically comprehensive, and best suited to traders who are willing to invest in manual entry in exchange for rich, flexible reporting. If you're a live trader who wants broker import and deep analytics, or if you don't trade from TradingView, Edgewonk earns its reputation.

TradeJour is a speed-first tool: purpose-built to reduce TradingView backtesting data entry to near-zero, with multi-screenshot support and cloud access designed for how modern backtesting traders actually work. If consistency has been your problem — if you have hundreds of unlogged backtests sitting in a screenshots folder somewhere — the friction reduction is real and meaningful.

The choice comes down to your workflow, not abstract features. If you backtest on TradingView and want to build a consistent logging habit, start your 14-day free trial of TradeJour → and see how many sessions you log before the trial ends.

More sessions logged means more data. More data means a real, provable edge. That's the whole point.

Related: The Professional's Guide to Manual Backtesting on TradingView