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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

Bottom quarter for its size
Per follower
0.011%
of 187K followers
Per impression
0.86%
2.4K views on a typical post
Reach
1.31%
of its followers see a post
Typical post
21
interactions (median)
Saved
0.123%
3 bookmarks on a typical post
Posting rate
0.7/day
active 53% of days
Peak time
16:00 UTC
Tuesday

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%.

p100.004%
p250.025%
p50 (median)0.146%
p750.694%
p902.61%
p9983.1%
Engagement rate as a share of followers, across the 212,146 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,455 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.025%
50th percentile0.146%
75th percentile0.694%
90th percentile2.61%
99th percentile83.1%

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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 16:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 16:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video71% of posts+111%+108% to +115%34K
Outbound link100% 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

    65242429.5K viewsView on X
  • 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

    4211013.4K viewsView on X
  • 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

    446104.5K viewsView on X
  • 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

    2461204.0K viewsView on X
  • 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

    252512.4K viewsView on X
  • 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

    219036.6K viewsView on X
  • 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

    238025.6K viewsView on X
  • 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

    254122.3K viewsView on X
  • 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

    264105.8K viewsView on X
  • 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

    219002.3K viewsView on X

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

#database#exadata

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.

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