MongoDB engagement report
@MongoDB - 503K followers on X
Measured over 34 original posts from a 30-day window, last computed on August 28, 2026.
Engagement
A typical post picks up 24 interactions against 503K followers, an engagement rate of 0.005%. Measured over 34 original posts, its engagement rate beats 22% of 3,739 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 6.7K times each, and 0.349% of those impressions turn into an interaction. That is about 1.34% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 67% of days. Most posts go out around 17:00 UTC, and Thursday is the busiest day of the week. Of the 34 posts sampled, 97% carry an image or video, 12% are part of a thread and 65% link out. The account's strongest tracked post pulled 89 interactions, about 3.7x its own typical post. Recurring topics include #mongodblocal, #lifeatmongodb, #mongodb.
Measured over 34 original posts from a 30-day window, last computed on August 28, 2026. Recurring tags: #mongodblocal, #lifeatmongodb, #mongodb.
Compared with accounts its own size
MongoDB's engagement rate beats 22% of the tracked X accounts closest to it in follower count (3,739 accounts, accounts of similar size (decile 7 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 26% 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 0.005%, MongoDB sits above the 10th percentile of the 36,261 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.012%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.431% |
| 90th percentile | 2.10% |
| 99th percentile | 160.7% |
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 17:00 UTC, and Thursday 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% | 50K |
| 01:00 UTC | -2% | 51K |
| 02:00 UTC | -3% | 50K |
| 03:00 UTC | -4% | 53K |
| 04:00 UTC | -6% | 43K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 48K |
| 07:00 UTC | -5% | 51K |
| 08:00 UTC | -4% | 60K |
| 09:00 UTC | -3% | 69K |
| 10:00 UTC | -2% | 71K |
| 11:00 UTC | -3% | 78K |
| 12:00 UTC | -2% | 86K |
| 13:00 UTC | -2% | 93K |
| 14:00 UTC | -3% | 96K |
| 15:00 UTC | -2% | 100K |
| 16:00 UTC | -3% | 97K |
| 17:00 UTC | -2% | 90K |
| 18:00 UTC | -1% | 84K |
| 19:00 UTC | -2% | 79K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -2% | 57K |
| 23:00 UTC | -2% | 51K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 229K |
| Monday | 0% | 284K |
| Tuesday | -2% | 273K |
| Wednesday | -1% | 250K |
| Thursday | -2% | 243K |
| Friday | -3% | 251K |
| Saturday | +3% | 226K |
Best tweets
- Aug 14, 20263.7x 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
- Aug 20, 20262.9x 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, 20262.9x 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
- Aug 14, 20262.4x their median
Congratulations to the winners of the Persistent Context Sprint Hackathon at #MongoDBlocal Build Fest! 🎉 🥇 Amelia: live captioning for deaf and hard-of-hearing users, separates speakers into voiceprints and remembers each person's identity, history, and commitments 🥈 TraceCase: reproduces a bug report across browsers, OS, and devices, then prepares the GitHub PR once the fix is verified 🥉 Perpetual: turns repeated agent routines into new skills, then pushes each one to every connected agent instantly via change streams Thank you to everyone who built and demoed, and to our partners, @cerebral_valley, for helping make the hackathon possible.
- Aug 13, 20262.2x their median
🌁 Builders are in San Francisco. 📍 So is MongoDB.local Build Fest. Join us for the latest innovations from MongoDB, live demos, major announcements, and conversations with the leaders building the future of production AI. ▶️ Watch live at 1PM PT: https://t.co/a59R0zzqSW #MongoDBlocal
- Aug 13, 20262.0x their median
“Too many organizations are running AI in production with an operational database, a vector store, a search engine, and embedding and reranking models, all from different vendors, bolted together instead of built for it. Now agents raise the bar. MongoDB was built as an operational platform from the start, so retrieval and memory run on the same live data, nothing to sync, and agents act on what's happening instantly.” MongoDB CTO, Jim Scharf, LIVE at #MongoDBlocal Build Fest.
- Aug 12, 20262.0x their median
Back to the Bay-sics: just laptops, caffeine, and 1 day until #MongoDBlocal Build Fest! ☕💻 Catch the livestream: https://t.co/fhm9xT53cu https://t.co/Ap5H1LZsQu
- Jul 17, 20261.9x their median
Most retrieval pipelines send too much to the LLM. Not because builders want them to, but because filtering low-relevance results used to mean adding a separate vendor, a new API, and more pipeline complexity. Most teams decide it isn't worth it. Native Reranking in MongoDB Atlas changes that. ⭐️ Now in public preview: a $rerank stage that runs inside the aggregation pipeline, powered by @VoyageAI by MongoDB, with no external round-trips. Up to 30% better retrieval quality on the MAIR benchmark, nothing added to your stack. See how native reranking fits your pipeline → https://t.co/usnfDiqrb4
- Aug 14, 20261.8x their median
“Observability works best when data flows freely,” Osmar Olivo, Senior Director of Database Product Management at MongoDB, says. “OpenTelemetry Metrics for Atlas brings MongoDB telemetry into your existing observability tools, making it easier to troubleshoot issues and keep applications running smoothly.” OpenTelemetry Metrics for Atlas connects database telemetry directly to the monitoring tools your team already uses every day. It’s open. It’s standardized. And it gives your team time back to focus on building, not troubleshooting. Unify your telemetry and cut through the operational noise. 👉 Learn how it works on the blog: https://t.co/nzGI5npxMo
- Aug 14, 20261.8x their median
Building an in-vehicle AI assistant means no room for lag, no room for guessing. Here at Build Fest, Rivian and Volkswagen Group Technologies's, Pranil Vora, is sharing how MongoDB powers Rivian Assistant with the speed and context-awareness driving demands. #MongoDBlocal https://t.co/qSRaSW6uHp
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.
Buy or sell X accounts - escrow-protected
PlayerSells is an escrow marketplace for X accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 24 interactions against 503K followers, an engagement rate of 0.005%. Measured over 34 original posts, its engagement rate beats 22% of 3,739 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 6.7K times each, and 0.349% of those impressions turn into an interaction. That is about 1.34% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 67% of days. Most posts go out around 17:00 UTC, and Thursday is the busiest day of the week. Of the 34 posts sampled, 97% carry an image or video, 12% are part of a thread and 65% link out. The account's strongest tracked post pulled 89 interactions, about 3.7x its own typical post. Recurring topics include #mongodblocal, #lifeatmongodb, #mongodb.
- What is MongoDB's engagement rate on X?
- MongoDB (@MongoDB) has an engagement rate of 0.005%, based on the median interactions across 34 original posts from the last 30 days against 503,358 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.005%, MongoDB sits above the 10th percentile of the 36,261 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 22% of the tracked X accounts closest to it in follower count (3,739 accounts), which puts it in the bottom quarter for its size 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 17:00 UTC, and Thursday is its busiest day, at roughly 1.5 posts per day across the measured window.