[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.] #  @BenjDicken Ben Dicken Ben Dicken posts on X about clickhouse, $googl, $380mo, $3600mo the most. They currently have XXXXX followers and XX posts still getting attention that total XXX engagements in the last XX hours. ### Engagements: XXX [#](/creator/twitter::1761964147510767616/interactions)  - X Week XXXXXXX +985% - X Month XXXXXXXXX +7,281% - X Months XXXXXXXXX -XX% - X Year XXXXXXXXXX +228,346% ### Mentions: X [#](/creator/twitter::1761964147510767616/posts_active)  - X Week XX +200% - X Month XX +33% - X Months XX +43% ### Followers: XXXXX [#](/creator/twitter::1761964147510767616/followers)  - X Week XXXXX +2.30% - X Month XXXXX +22% - X Months XXXXX +55% - X Year XXXXX +1,324% ### CreatorRank: XXXXXXXXX [#](/creator/twitter::1761964147510767616/influencer_rank)  ### Social Influence [#](/creator/twitter::1761964147510767616/influence) --- **Social category influence** [technology brands](/list/technology-brands) XXXXX% [stocks](/list/stocks) XXXX% **Social topic influence** [clickhouse](/topic/clickhouse) 5.88%, [$googl](/topic/$googl) 5.88%, [$380mo](/topic/$380mo) 5.88%, [$3600mo](/topic/$3600mo) XXXX% **Top accounts mentioned or mentioned by** [@chris14978335](/creator/undefined) [@richobray](/creator/undefined) [@erikhofvander](/creator/undefined) [@terrorobe](/creator/undefined) [@rixer_inc](/creator/undefined) [@tylerhillery](/creator/undefined) [@rixerinc](/creator/undefined) [@emrahdma](/creator/undefined) [@planetscale](/creator/undefined) [@mitsuhiko](/creator/undefined) [@jarredsumner](/creator/undefined) [@toniievych](/creator/undefined) [@dizzzmas](/creator/undefined) [@_tylerhillery](/creator/undefined) [@0x15f](/creator/undefined) **Top assets mentioned** [Alphabet Inc Class A (GOOGL)](/topic/$googl) ### Top Social Posts [#](/creator/twitter::1761964147510767616/posts) --- Top posts by engagements in the last XX hours "Today I'm reading the original log-structured merge-tree paper. LSM trees were designed to reduce IO cost for high-volume write-heavy database workloads. This came out in 1996 and today it's widely used by databases like DynamoDB ClickHouse and Google Bigtable"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1937553103299203345) 2025-06-24 16:47:12 UTC 9834 followers, 15.1K engagements "io2 on the other hand offers excellent performance and great durability but it has a huge price tag. EG: 1tb io2 ebs volume with 64k iops = $3600/mo i7ie.xlarge with 2.5tb ssd and 100k iops = $380/mo"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947344515179942090) 2025-07-21 17:14:46 UTC 9834 followers, XXX engagements "Many cloud databases run on network-attached storage the most popular of which is AWS EBS specifically gp3 and io2. The larger IOPS max you set the more you pay"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947344511899996664) 2025-07-21 17:14:46 UTC 9833 followers, 1004 engagements "LSM trees use multiple layers and batched writes to improve efficiency. Data is first inserted into the sequential log (for recovery) and an in-memory tree. It only gets persisted to the on-disk B-tree in sequential batches"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1937556932614848914) 2025-06-24 17:02:25 UTC 9807 followers, XXX engagements "@rixer_inc If your entire database can fit in RAM you won't notice as much of a difference except for writes. But this is rarely the case for large-scale databases"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947671361360732621) 2025-07-22 14:53:33 UTC 9820 followers, XXX engagements "IOPS capacity is a critical consideration for high-performance databases. Yet many don't understand what they are how they impact performance and their costs. Let's take deep dive: What are IOPS"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947344505864393205) 2025-07-21 17:14:44 UTC 9834 followers, 17.1K engagements "The latency between even two "nearby" regions like us-east X and X is 18ms. us-east-1 to us-west-1 is closer to 60ms. This advice is spot on. Do yourself a favor and keep your database in the same region as your other infra. Better yet same AZ"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947641754640941353) 2025-07-22 12:55:54 UTC 9834 followers, 178.2K engagements
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
Ben Dicken posts on X about clickhouse, $googl, $380mo, $3600mo the most. They currently have XXXXX followers and XX posts still getting attention that total XXX engagements in the last XX hours.
Social category influence technology brands XXXXX% stocks XXXX%
Social topic influence clickhouse 5.88%, $googl 5.88%, $380mo 5.88%, $3600mo XXXX%
Top accounts mentioned or mentioned by @chris14978335 @richobray @erikhofvander @terrorobe @rixer_inc @tylerhillery @rixerinc @emrahdma @planetscale @mitsuhiko @jarredsumner @toniievych @dizzzmas @_tylerhillery @0x15f
Top assets mentioned Alphabet Inc Class A (GOOGL)
Top posts by engagements in the last XX hours
"Today I'm reading the original log-structured merge-tree paper. LSM trees were designed to reduce IO cost for high-volume write-heavy database workloads. This came out in 1996 and today it's widely used by databases like DynamoDB ClickHouse and Google Bigtable" @BenjDicken on X 2025-06-24 16:47:12 UTC 9834 followers, 15.1K engagements
"io2 on the other hand offers excellent performance and great durability but it has a huge price tag. EG: 1tb io2 ebs volume with 64k iops = $3600/mo i7ie.xlarge with 2.5tb ssd and 100k iops = $380/mo" @BenjDicken on X 2025-07-21 17:14:46 UTC 9834 followers, XXX engagements
"Many cloud databases run on network-attached storage the most popular of which is AWS EBS specifically gp3 and io2. The larger IOPS max you set the more you pay" @BenjDicken on X 2025-07-21 17:14:46 UTC 9833 followers, 1004 engagements
"LSM trees use multiple layers and batched writes to improve efficiency. Data is first inserted into the sequential log (for recovery) and an in-memory tree. It only gets persisted to the on-disk B-tree in sequential batches" @BenjDicken on X 2025-06-24 17:02:25 UTC 9807 followers, XXX engagements
"@rixer_inc If your entire database can fit in RAM you won't notice as much of a difference except for writes. But this is rarely the case for large-scale databases" @BenjDicken on X 2025-07-22 14:53:33 UTC 9820 followers, XXX engagements
"IOPS capacity is a critical consideration for high-performance databases. Yet many don't understand what they are how they impact performance and their costs. Let's take deep dive: What are IOPS" @BenjDicken on X 2025-07-21 17:14:44 UTC 9834 followers, 17.1K engagements
"The latency between even two "nearby" regions like us-east X and X is 18ms. us-east-1 to us-west-1 is closer to 60ms. This advice is spot on. Do yourself a favor and keep your database in the same region as your other infra. Better yet same AZ" @BenjDicken on X 2025-07-22 12:55:54 UTC 9834 followers, 178.2K engagements
/creator/twitter::BenjDicken