[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, theres a, $380mo the most. They currently have XXXXX followers and XX posts still getting attention that total XXX engagements in the last XX hours. ### Engagements: XXX [#](/creator/twitter::1761964147510767616/interactions)  - X Week XXXXXXX +158% - X Month XXXXXXXXX +10,447% - X Months XXXXXXXXX -XX% - X Year XXXXXXXXXX +222,255% ### Mentions: XX [#](/creator/twitter::1761964147510767616/posts_active)  - X Months XX -XX% ### Followers: XXXXX [#](/creator/twitter::1761964147510767616/followers)  - X Week XXXXX +2.50% - X Month XXXXX +21% - X Months XXXXX +54% - X Year XXXXX +1,318% ### CreatorRank: XXXXXXXXX [#](/creator/twitter::1761964147510767616/influencer_rank)  ### Social Influence [#](/creator/twitter::1761964147510767616/influence) --- **Social category influence** [technology brands](/list/technology-brands) [stocks](/list/stocks) **Social topic influence** [clickhouse](/topic/clickhouse), [$googl](/topic/$googl), [theres a](/topic/theres-a), [$380mo](/topic/$380mo), [100k](/topic/100k), [$3600mo](/topic/$3600mo), [affordable](/topic/affordable) **Top assets mentioned** [Alphabet Inc Class A (GOOGL)](/topic/$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 9796 followers, 15.1K engagements "@chris14978335 There's a difference between the AZ label you see in your AWS console and the actual physical availability zone. In that visual I used the physical AZ IDs. Read more here:"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947885969728016577) 2025-07-23 05:06:19 UTC 9792 followers, XX 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 9721 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 9721 followers, XXX 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 9791 followers, XXX engagements "@RichOBray That makes more sense 16mm is quite wide but with that level of crop it becomes more reasonable"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947716896696242229) 2025-07-22 17:54:29 UTC 9790 followers, XX 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 9792 followers, XXX engagements "The best way to maximize IOPS are using local NVMe SSDs. You get access to modern high-bandwidth and low-latency storage technology without no network or throttling in-between. This is what we use for @PlanetScale Metal to achieve best-in-class performance"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947344509362123010) 2025-07-21 17:14:45 UTC 9776 followers, 1069 engagements "Can't get over how great the postgres metrics reporting is. The observability we're giving our users is off the charts"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1946303641478189280) 2025-07-18 20:18:43 UTC 9791 followers, 10.3K 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 9796 followers, 17K engagements "gp3 is the more affordable option but has lower durability and performance guarantees than io2. These are a great option for database workloads with lower I/O demand but become a bottleneck for high I/O workloads"  [@BenjDicken](/creator/x/BenjDicken) on [X](/post/tweet/1947344513820987679) 2025-07-21 17:14:46 UTC 9721 followers, XXX 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 9796 followers, 177.9K 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.]
@BenjDicken Ben Dicken
Ben Dicken posts on X about clickhouse, $googl, theres a, $380mo the most. They currently have XXXXX followers and XX posts still getting attention that total XXX engagements in the last XX hours.
Engagements: XXX #
- X Week XXXXXXX +158%
- X Month XXXXXXXXX +10,447%
- X Months XXXXXXXXX -XX%
- X Year XXXXXXXXXX +222,255%
Mentions: XX #
- X Months XX -XX%
Followers: XXXXX #
- X Week XXXXX +2.50%
- X Month XXXXX +21%
- X Months XXXXX +54%
- X Year XXXXX +1,318%
CreatorRank: XXXXXXXXX #
Social Influence #
Social category influence technology brands stocks
Social topic influence clickhouse, $googl, theres a, $380mo, 100k, $3600mo, affordable
Top assets mentioned Alphabet Inc Class A (GOOGL)
Top Social 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 on X 2025-06-24 16:47:12 UTC 9796 followers, 15.1K engagements
"@chris14978335 There's a difference between the AZ label you see in your AWS console and the actual physical availability zone. In that visual I used the physical AZ IDs. Read more here:" @BenjDicken on X 2025-07-23 05:06:19 UTC 9792 followers, XX 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 9721 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 9721 followers, XXX 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 9791 followers, XXX engagements
"@RichOBray That makes more sense 16mm is quite wide but with that level of crop it becomes more reasonable" @BenjDicken on X 2025-07-22 17:54:29 UTC 9790 followers, XX 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 9792 followers, XXX engagements
"The best way to maximize IOPS are using local NVMe SSDs. You get access to modern high-bandwidth and low-latency storage technology without no network or throttling in-between. This is what we use for @PlanetScale Metal to achieve best-in-class performance" @BenjDicken on X 2025-07-21 17:14:45 UTC 9776 followers, 1069 engagements
"Can't get over how great the postgres metrics reporting is. The observability we're giving our users is off the charts" @BenjDicken on X 2025-07-18 20:18:43 UTC 9791 followers, 10.3K 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 9796 followers, 17K engagements
"gp3 is the more affordable option but has lower durability and performance guarantees than io2. These are a great option for database workloads with lower I/O demand but become a bottleneck for high I/O workloads" @BenjDicken on X 2025-07-21 17:14:46 UTC 9721 followers, XXX 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 9796 followers, 177.9K engagements