ScyllaDB (@ScyllaDB) on YouTube

Updated 2026-07-31

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ScyllaDB is a creator on YouTube in the 9K–10K follower range, publishing for Performance engineers, backend developers and database specialists at tech companies building high-scale, low-latency NoSQL and big data systems, based in United States. Profile last checked 2026-07-31.

Observed facts (from the public profile):

FieldValue
PlatformYouTube
Handle@ScyllaDB
Followers9K–10K
Indexed underSoftware · Developer tools / infra
MarketUnited States
Audience functiondevelopers

Profile bio

Welcome to the ScyllaDB YouTube Channel! You'll find videos on NoSQL and big data topics from experts in the field.

What this creator posts about, and who reads it (AI-inferred)

Recurring topics: P99 latency optimization, NoSQL database performance, ScyllaDB features and use cases, Real-time feature stores, Vector search in databases

Audience: Performance engineers, backend developers and database specialists at tech companies building high-scale, low-latency NoSQL and big data systems

Provenance: inferred by AI from public content, not stated by the creator — confidence 0.75 · read from 45 recent posts · updated 79 days ago.

Audience read from this creator’s own recent posts, not from platform-declared categories. It is our reading, and it can be wrong.

Recent content samples (what the inference above was drawn from)

P99 CONF 2026 - Dor Laor, CEO and Co-Founder of ScyllaDB
P99 CONF 2026 - Ershaad Basheer, Computing Systems Engineer at Lawrence Berkeley National Laboratory
P99 CONF 2026 - Cong Wang, Founder and CEO of Multikernel Technologies
Optimizing Write-Intensive Masterclass / August 26, 2026

Where this creator sits among comparable accounts

Compared with the 1,605 accounts in the same group (youtube · nano · software):

DimensionPercentile in group
Overall93rd
Authenticity98th
Audience value52nd
Focus & activity88th

This is a position, not a verdict. A percentile says where this account falls among comparable accounts on signals we can measure — it does not say this creator is a better fit for your campaign. We ran a blind benchmark and measured no reliable advantage in selection quality, and do not claim one.

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Machine-readable representations

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AI retrieval activity

What AI systems have actually done with this page. The two kinds are counted separately: being indexed is not the same as being used.

KindRequestsWhat it means
Indexing crawlers8Bulk indexing · Amazonbot, Applebot, ClaudeBot, Meta, PerplexityBot
User-triggered retrievals0none recorded yet

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