Oracle AI Database engagement report
@OracleDatabase - 187K followers on X
Measured over 21 original posts from a 30-day window, last computed on October 13, 2026.
Engagement
A typical post picks up 21 interactions against 187K followers, an engagement rate of 0.011%. Measured over 21 original posts, its engagement rate beats 25% of 21,185 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 2.4K times each, and 0.86% of those impressions turn into an interaction. That is about 1.31% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.7 post a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 21 posts sampled, 71% carry an image or video and 100% link out. The account's strongest tracked post pulled 115 interactions, about 5.5x its own typical post. Recurring topics include #database, #exadata.
Measured over 21 original posts from a 30-day window, last computed on October 13, 2026. Recurring tags: #database, #exadata.
Compared with accounts its own size
Oracle AI Database's engagement rate beats 25% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 9 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 39% 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 0.011%, Oracle AI Database sits above the 10th percentile of the 212,146 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.694% |
| 90th percentile | 2.61% |
| 99th percentile | 83.1% |
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 16:00 UTC, and Tuesday 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 | 71% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 71% 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.
- 100% 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 409 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
- Oct 14, 20255.5x their median
By architecting AI and data together, our AI Database makes ‘AI for Data’ simple to learn and use. https://t.co/US2iUsuJfe #AIWorld https://t.co/2tb9uggEQT
- Aug 21, 20262.6x their median
25 years of Oracle RAC, built for what’s next. Run diverse workloads as one clustered database with capabilities designed to support continuous availability, scalability, and operational simplicity—on Exadata across on-premises, OCI, Oracle Database@AWS, Oracle Database@Azure, and Oracle Database@Google Cloud. Learn more: https://t.co/WcaQtcG4l4
- Oct 6, 20262.4x their median
Going to Oracle AI World? Add the Codex + Oracle AI Database Hackathon to your Wednesday morning: two hours, your idea, OpenAI Codex and Oracle AI Database experts in the room. Seats are limited and registration is separate from your AI World pass. Request your seat, session HAC1394: https://t.co/Zc84sswhDC
- Aug 15, 20262.0x their median
Oracle Exadata Database Service on Exascale Infrastructure is now available for Oracle AI Database@AWS. Start small with a VM cluster and scale as you grow, paying only for what you use while getting Exadata performance at a lower entry cost. Available now in US East (N. Virginia), US West (Oregon), EU Central (Frankfurt), and expanding soon to all 22 Regions. https://t.co/kkoz6hTOFS
- Sep 15, 20261.6x their median
Oracle APEX AI Application Generator frees you from business bottlenecks, putting AI to work on your enterprise data to quickly deliver apps, answers, and actions. Explore release resources at https://t.co/r87EnsKS3o https://t.co/H5VFkhuT6e
- Sep 9, 20261.6x their median
Join one of our upcoming info sessions to discover how Oracle AI Database can run everywhere in the cloud of your choice. Bring your questions and leave with a clearer path for your priority workloads and practical next steps. https://t.co/8By16pW2WC https://t.co/9bUv5OmQfQ
- Jul 27, 20261.6x their median
The next wave of enterprise AI won't be won by the best model—it will be won by the best data architecture. See why @ChiefDS at theCUBE Research says Oracle is the operational brain for agentic AI. Read the analysis: https://t.co/JM75LGcwV6
- Sep 16, 20261.5x their median
Why do app developers love Oracle True Cache? It’s a built-in feature of @Oracle AI Database that can help boost #database read performance by offloading any type of query, including AI vectors for semantic search and RAG from production databases. Read the blog https://t.co/BU2xYMWpL6
- Oct 7, 2026
The more autonomous AI becomes, the more important human accountability becomes. Oracle’s CISO explains why AI security governance must combine human oversight with foundational controls such as least privilege, authorization, segmentation, and monitoring. AI can accelerate the work, but people remain responsible for the guardrails. How do you scale agentic AI without scaling risk? Read the full SiliconANGLE analysis and watch the interview with Brennan Baybeck: https://t.co/SEMA8004uN
- Sep 8, 2026
Oracle APEX enables AI-generated apps at machine speed—without inheriting the security, governance, or maintenance tradeoffs of code generation. @holgermu notes that “Oracle APEX AI Application Generator is the proverbial no-brainer to adopt for any Oracle AI Database customers looking for a proven and fast way to build AI-powered applications.” Read his report: https://t.co/4jDAVECs92
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 21 interactions against 187K followers, an engagement rate of 0.011%. Measured over 21 original posts, its engagement rate beats 25% of 21,185 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 2.4K times each, and 0.86% of those impressions turn into an interaction. That is about 1.31% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.7 post a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 21 posts sampled, 71% carry an image or video and 100% link out. The account's strongest tracked post pulled 115 interactions, about 5.5x its own typical post. Recurring topics include #database, #exadata.
- What is Oracle AI Database's engagement rate on X?
- Oracle AI Database (@OracleDatabase) has an engagement rate of 0.011%, based on the median interactions across 21 original posts from the last 30 days against 186,917 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.011%, Oracle AI Database sits above the 10th percentile of the 212,146 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 @OracleDatabase have real engagement?
- Its engagement rate beats 25% of the tracked X accounts closest to it in follower count (21,185 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 @OracleDatabase post?
- Most posts go out around 16:00 UTC, and Tuesday is its busiest day, at roughly 0.7 posts per day across the measured window.