ByteByteGo

Subscribers 1.4M

Videos 163

Views 59.3M

Channels Like ByteByteGo

ByteByteGo covers topics and trends in large-scale system design, including tutorials and deep-dives on distributed systems, data stores, and design patterns. Content appears as instructional videos and explanatory breakdowns (e.g., system design interviews, design of specific systems, and technology explainers) with an emphasis on topics like Kafka, Redis, URL shorteners, and web crawlers. The channel publishes new videos regularly, with an average view count around 107.2K per video and total metrics showing 1.4M subscribers and 59.3M total views across 163 videos.

Results last updated 3 months ago.

Similar Channels

We found 49 YouTube channels similar to ByteByteGo

#1

ByteMonk view on YouTube ▶

89% relevance

Subscribers 337K

Videos 492

Views 14.0M

Appearances 23

SERP 100%

Similarity 81%

distributed systems design designing scalable systems rate limiter design

Both target system design and scalable architecture topics with high search overlap on queries like distributed systems design and rate limiter design; ByteMonk’s content similarly centers on deep technical guidance, aligning with ByteByteGo’s audience (89% search match, 81% content).

#2

Hello Interview - SWE Interview Preparation

83% relevance

Subscribers 169K

Videos 79

Views 7.4M

Appearances 18

SERP 81%

Similarity 85%

system design interview distributed systems design designing scalable systems

Shares a strong focus on system design interviews and distributed systems design, matching ByteByteGo on core questions such as system design interview and designing scalable systems (81% search, 85% content).

#3

Exponent

76% relevance

Subscribers 481K

Videos 730

Views 27.0M

Appearances 13

SERP 82%

Similarity 73%

system design interview distributed systems design designing scalable systems

Targets system design interviews and distributed systems design with substantial overlap in queries like system design interview and designing scalable systems, aligning with ByteByteGo’s practical design-focused guidance (82% search, 73% content).

#4

Hayk Simonyan

70% relevance

Subscribers 98.7K

Videos 129

Views 3.4M

Appearances 13

SERP 54%

Similarity 80%

system design interview designing scalable systems data store architecture

Competes in system design interview and scalable systems topics and adds data store architecture, creating overlap in queries and content style though with some emphasis on data storage patterns (54% search, 80% content).

#5

Gaurav Sen

70% relevance

Subscribers 722K

Videos 422

Views 43.8M

Appearances 18

SERP 60%

Similarity 76%

system design interview distributed systems design designing scalable systems

Covers system design interviews and distributed systems design with similar instructional approach and example-driven explanations, matching ByteByteGo’s audience on core topics (60% search, 76% content).

#6

CodeLucky view on YouTube ▶

64% relevance

Subscribers 7.4K

Videos 10K

Views 1.1M

Appearances 16

SERP 65%

Similarity 64%

key value store stream processing design database design patterns

Focuses on key-value stores, stream processing design, and database design patterns, which align with ByteByteGo’s practical architecture topics, though with relatively balanced search and content similarity (65% search, 64% content).

Content Landscape

Top competitors identified by match strength are ByteMonk (89% match) and Hello Interview - SWE Interview Preparation (83% match). Exponent (76% match) also closely aligns. These channels share overlapping queries with ByteByteGo such as system design interview, distributed systems design, and designing scalable systems. ByteMonk has 337K subscribers and Hello Interview has 169K subscribers, both smaller than ByteByteGo’s 1.4M, while Exponent has 481K subscribers, also smaller but notable in the same topic space. All three competitors, like ByteByteGo, focus on system design topics and interview preparation, with overlaps on queries related to distributed systems, rate limiter design, and scalable architecture.

Video Highlights

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Search Queries Used

system design interview large scale systems distributed systems design designing scalable systems data store architecture message queue design web crawler design rate limiter design key value store URL shortener architecture pubsub systems design stream processing design cache architecture design web application architecture database design patterns scalability patterns distributed systems patterns system design tradeoffs consistency models overview event-driven architecture design microservices architecture patterns database sharding strategies data partitioning techniques leader election algorithms high availability design observability in systems fault tolerance techniques concurrency control methods cache invalidation strategies data replication methods stream processing architectures batch vs streaming processing CDN architecture basics queueing theory in design appliance for data warehousing

Frequently Asked Questions

Which YouTube channels are most similar to ByteByteGo?

ByteMonk — 89% match, 337K subscribers; Hello Interview - SWE Interview Preparation — 83% match, 169K subscribers; Exponent — 76% match, 481K subscribers. All three channels are educational YouTube channels focusing on software engineering interview prep and tech concepts, overlapping with ByteByteGo in topics like system design, algorithms, and tech tutorials.

What type of content does ByteByteGo make?

ByteByteGo creates educational videos about software engineering interviews and technical concepts, with titles such as How to Crack Any System Design Interview (677.9K views), Transformers Step-by-Step Explained (55.9K views), and What Is Redis Really About? Why Is It So Popular? (66.4K views). The channel has about 1.4M subscribers and an average of 107.2K views per video, with multiple uploads per week.

How do we determine which channels are similar to ByteByteGo?

We analyze ByteByteGo's recent videos, generate topic-relevant search queries, check YouTube search results, and compare the meaning of each channel's content to measure similarity. The result is a ranked list sorted by SERP overlap, semantic similarity, and search appearances.

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