MongoDB engagement report
@MongoDB - 504K followers on X
Measured over 32 original posts from a 30-day window, last computed on October 19, 2026.
Engagement
A typical post picks up 33 interactions against 504K followers, an engagement rate of 0.007%. Measured over 32 original posts, its engagement rate beats 28% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 5.2K times each, and 0.629% of those impressions turn into an interaction. That is about 1.04% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 32 posts sampled, 91% carry an image or video, 6% are part of a thread and 66% link out. The account's strongest tracked post pulled 179 interactions, about 5.4x its own typical post.
Measured over 32 original posts from a 30-day window, last computed on October 19, 2026. Recurring tag: #mongodblocal.
Compared with accounts its own size
MongoDB's engagement rate beats 28% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 36% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.007%, MongoDB sits above the 10th percentile of the 204,956 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 19:00 UTC, and Wednesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 91% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 66% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 91% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 66% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 435 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 29, 20265.4x their median
Back at @Nasdaq! MongoDB's @dittycheria rang the opening bell in celebration of our latest announcements and tomorrow's MongoDB.local NYC. 🎉 https://t.co/BaXvCX1pIX
- Sep 29, 20263.5x their median
An agent can reason perfectly and still make the wrong call if its data is stale. As AI moves from generating answers to taking action, the data layer needs to keep up. Today, we’re announcing the largest expansion of our platform yet: ✨ MongoDB 9.0: the fastest, most performant version of MongoDB we’ve ever built, designed for applications and agents that act on live data. ✨ Atlas Infinite: a new deployment option built for highly elastic workloads, allowing storage and compute to scale independently as demand changes. ✨ Atlas Agent Engine: provides the memory, runtime, and governance needed to operate agents in production, on the same data foundation customers already trust and open to any model, framework, or cloud. Learn more: https://t.co/OtHBZLd5yU
- Aug 14, 20263.3x their median
AI development is moving fast. Your data platform should, too. Today at #MongoDBlocal Build Fest, we're introducing new MongoDB Atlas capabilities that help you: 💬 Work natively inside leading AI tools ✨ Give agents governed access to live data 🧠 Auto-embed #1-ranked Voyage AI embeddings ⚡ Enrich real-time streaming data with vector search 📊 Stream metrics straight to your observability stack Everything you need to build smarter AI applications—now in MongoDB Atlas. Learn more about building in the agentic era: https://t.co/c9yRai3GcP Learn more about our advances in industry-leading retrieval: https://t.co/10qDc2993g
- Sep 30, 20262.7x their median
AI is moving from generating answers to taking action. Your data platform should move with it. At #MongoDBlocal NYC, we announced the biggest expansion of the MongoDB platform yet. New capabilities help you: 🚀 Run on MongoDB 9.0, now GA with up to 2x higher throughput ♾️ Scale compute and storage independently with Atlas Infinite 🤖 Build, deploy, and govern agents on live data with Atlas Agent Engine ⏱️ Let agents spin up databases in seconds with Ephemeral Clusters 🔐 Run prefix, suffix, and substring queries on fully encrypted data 🎯 Rerank results in the aggregation pipeline with Voyage AI rerank-3 Everything you need to take AI apps and agents to production, on one intelligent data platform. https://t.co/GaFCthaIzB
- Sep 30, 20262.2x their median
Before we sell agentic AI to anyone else, we put it to work on ourselves. Holly is MongoDB's internal AI assistant, built on Atlas Agent Engine, designed to connect the tools our sales team already uses into one workspace, instead of ten. What it's done for research time, deal prep, and account strategy might surprise you. ✨ Read the full use case here: https://t.co/PvFeihalxu
- Aug 20, 20262.2x their median
ICYMI: Everything announced at #MongoDBlocal Build Fest is designed to help developers stay in flow and ship production AI, faster. From the new Atlas Managed MCP Server for Agents and native Atlas access inside @claudeai, Claude Code, @ChatGPT, Codex, @grok Build, @DevinAI, & @cursor_ai, to Automated Embeddings in MongoDB Atlas and @VoyageAI's voyage-code-4, plus a GA'd Embedding & Reranking API and Vector Search for Stream Processing, it's about less setup, fewer workarounds, and more time building. Get the latest: https://t.co/YGX7MGq0oN @swyx @BazeleyMikiko
- Aug 13, 20262.1x their median
"Once you have a system that can run for a month at a time, I think our relationship with computing will change pretty fast," said @jxnlco, Developer Experience Engineer at @OpenAI. "Your job is to understand what success looks like and give your models superior access to the data they need to get the job done." Liu joined MongoDB CTO, Jim Scharf, for a conversation on building production-grade AI agents. #MongoDBlocal
- Sep 30, 20261.9x their median
Building an AI agent demo is one thing. Building a system your business can depend on takes more. “You can’t just throw $100,000 at a tough programming challenge and actually have it build production software.” — @walden_yan, Co-Founder & CPO, @cognition At #MongoDBlocal NYC, leaders from @cognition, @temporalio, and @openrouter joined @sophiadew for “Building at the Frontier”—a candid conversation about what it takes to run AI agents in production, from testing and verification to recovering from failures and controlling access to data. The takeaway: As agents gain autonomy, the data layer matters more than ever. Watch the full session: https://t.co/dUbzpFdspH
- Sep 1, 20261.9x their median
MongoDB just announced Q2 FY2027 earnings. 📈 Total revenue of $772M, up 30% YoY. ☁️ MongoDB Atlas revenue grew ~29% YoY 🚀 EA & Other revenue grew 36% YoY 🤝 2,900 additional customers for a total of more than 70,600 total customers 🔍 @VoyageAI customers nearly doubled QoQ We are raising full-year 2027 guidance due to strength in MongoDB Atlas. Learn more: https://t.co/2cyxvnHkYx
- Sep 30, 20261.8x their median
Quality context is the difference between effective AI agents and reliable ones. This week, we made Voyage AI’s industry-leading embedding and reranking models even better. 🧵👇 Here’s what’s new https://t.co/pEF2NTLa1U
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 33 interactions against 504K followers, an engagement rate of 0.007%. Measured over 32 original posts, its engagement rate beats 28% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 5.2K times each, and 0.629% of those impressions turn into an interaction. That is about 1.04% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 32 posts sampled, 91% carry an image or video, 6% are part of a thread and 66% link out. The account's strongest tracked post pulled 179 interactions, about 5.4x its own typical post.
- What is MongoDB's engagement rate on X?
- MongoDB (@MongoDB) has an engagement rate of 0.007%, based on the median interactions across 32 original posts from the last 30 days against 503,864 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.007%, MongoDB sits above the 10th percentile of the 204,956 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @MongoDB have real engagement?
- Its engagement rate beats 28% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @MongoDB post?
- Most posts go out around 19:00 UTC, and Wednesday is its busiest day, at roughly 1.57 posts per day across the measured window.