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Oracle Developers engagement report

@OracleDevs - 117K followers on X

Measured over 38 original posts from a 30-day window, last computed on October 7, 2026.

Engagement

Middle of its size range
Per follower
0.021%
of 117K followers
Per impression
1.20%
2.0K views on a typical post
Reach
1.74%
of its followers see a post
Typical post
24
interactions (median)
Saved
0.172%
4 bookmarks on a typical post
Posting rate
1.33/day
active 73% of days
Peak time
14:00 UTC
Tuesday

A typical post picks up 24 interactions against 117K followers, an engagement rate of 0.021%. Measured over 38 original posts, its engagement rate beats 27% of 15,519 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 2.0K times each, and 1.20% of those impressions turn into an interaction. That is about 1.74% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.3 post a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 38 posts sampled, 89% carry an image or video and 89% link out. The account's strongest tracked post pulled 259 interactions, about 11x its own typical post. Recurring topics include #aiworld, #java27, #orclapex.

Measured over 38 original posts from a 30-day window, last computed on October 7, 2026. Recurring tags: #aiworld, #java27, #orclapex.

Compared with accounts its own size

Oracle Developers's engagement rate beats 27% of the tracked X accounts closest to it in follower count (15,519 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 45% 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 0.021%, Oracle Developers sits above the 10th percentile of the 156,839 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.022%.

p100.003%
p250.022%
p50 (median)0.128%
p750.604%
p902.32%
p9983.4%
Engagement rate as a share of followers, across the 156,839 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 26,058 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 percentile0.003%
25th percentile0.022%
50th percentile0.128%
75th percentile0.604%
90th percentile2.32%
99th percentile83.4%

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 14:00 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: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 14:00 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 video89% of posts+111%+108% to +115%34K
Outbound link89% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 89% 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.
  • 89% 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 318 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 15, 202611x their median

    #Java27 has arrived! 🥳☕ Get all the details about the latest release from our Java team. https://t.co/u2bfScIyn1 https://t.co/rt0A4gc5oa

    20650126.0K viewsView on X
  • Oct 3, 20262.5x their median

    Antigravity sits near a developer’s real work: code, terminal commands, notebooks, configuration, and implementation details. Learn how to build an Antigravity workflow with the Oracle SQLcl MCP Server and Oracle AI Database that allows you to see what Antigravity asked for, which tool path ran, what the database allowed, which memory records were retrieved, and how the final answer was assembled. https://t.co/XhF0UOHOrL

    506303.9K viewsView on X
  • Sep 20, 20262.1x their median

    Try Oracle REST Data Services with docker compose for a repeatable, local development environment. Anders Swanson explains why it's great if you're building with ORDS and want a dev/test stack with easy setup and teardown. Initialization SQL can be fully customized and may optionally install APEX if you're an APEX user. #orclAPEX

    406313.6K viewsView on X
  • Sep 19, 20261.9x their median

    To handle bursty, mission-critical workloads without overspending on idle cloud capacity, architects need a decoupled, event-driven framework. That's why we introduced a reference architecture built on OCI designed to improve throughput while reducing avoidable compute, storage, and data movement costs. Learn more: https://t.co/qNoebn1odh

    414003.5K viewsView on X
  • Oct 2, 20261.8x their median

    Looking to reduce PostgreSQL replication latency? We show how PostgreSQL-native pglogical helped a global security platform team achieve replication latency of approximately one to two seconds. 😱 https://t.co/8fHtqjNitr https://t.co/GoMDfhESHv

    356102.6K viewsView on X
  • Sep 16, 20261.6x their median

    How do you generate vector embeddings for an AI application? We explain what vectors are, how embeddings are generated, and which ONNX embedding models can be used directly with Oracle AI Database. https://t.co/CX887mpTAP

    307204.0K viewsView on X
  • Sep 24, 20261.6x their median

    Spacebank’s RoboViewX utilizes Oracle APEX as its operational infrastructure—serving as a unified control center for complex robot fleets. 🤖 See how APEX allowed it to achieve a 60%+ improvement in development velocity, reduce delivery cycles to 2–4 weeks, improve scalability across hybrid deployments, and more. #orclAPEX https://t.co/tpgJIa09JB

    353002.4K viewsView on X
  • Sep 29, 2026

    As AI agents evolve beyond chat, developers need secure ways to connect models, enterprise data, and dynamic user interfaces. We demonstrate how to build A2UI and MCP Apps using Oracle AI Database and the Java MCP Toolkit, with examples that run in ChatGPT, Claude, and Google Gemini Enterprise. You'll learn: 👉 How to expose governed database capabilities through the Java MCP Toolkit instead of unrestricted database access 👉 When to use A2UI for host-native, declarative interfaces versus MCP Apps for portable, sandboxed web experiences 👉 How Oracle AI Database remains the authoritative layer for validation, transactions, and auditing while AI agents provide rich user experiences 👉 End-to-end architecture, deployment guidance, and complete reference code to accelerate your own agentic AI applications Check out this comprehensive walkthrough to get practical examples of MCP, A2UI, Oracle AI Database, agentic AI architecture, and enterprise AI application development: https://t.co/o5joDXCjEC

    283211.8K viewsView on X
  • Sep 18, 2026

    Our new short course with @DeepLearningAI covers continual and adaptive learning: the different ways in which you can make an agent better over time, and how to do it on Oracle AI Database 26ai. We go over the details: https://t.co/usONCAljuC https://t.co/2XcVAkFBAL

    311102.3K viewsView on X
  • Oct 2, 2026

    By combining Oracle Kubernetes Engine, kagent, OCI Generative AI, and OCI DevOps, organizations can build a more intelligent and governed operations model. The result isn't just faster diagnosis, but better decision-making. Incidents are evaluated with context, remediations are controlled, and business-critical applications can be protected with greater confidence. This blog breaks it down: https://t.co/YJeUVfFcqH

    254202.1K 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

#aiworld#java27#orclapex

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 24 interactions against 117K followers, an engagement rate of 0.021%. Measured over 38 original posts, its engagement rate beats 27% of 15,519 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 2.0K times each, and 1.20% of those impressions turn into an interaction. That is about 1.74% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.3 post a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 38 posts sampled, 89% carry an image or video and 89% link out. The account's strongest tracked post pulled 259 interactions, about 11x its own typical post. Recurring topics include #aiworld, #java27, #orclapex.

What is Oracle Developers's engagement rate on X?
Oracle Developers (@OracleDevs) has an engagement rate of 0.021%, based on the median interactions across 38 original posts from the last 30 days against 117,054 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.021%, Oracle Developers sits above the 10th percentile of the 156,839 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 @OracleDevs have real engagement?
Its engagement rate beats 27% of the tracked X accounts closest to it in follower count (15,519 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 @OracleDevs post?
Most posts go out around 14:00 UTC, and Tuesday is its busiest day, at roughly 1.33 posts per day across the measured window.

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