If you run a MySQL-backed application, this pattern is probably familiar:<\/p>\n\n\n\n
GROUP BY<\/code> queries.<\/li>\n\n\n\n- API endpoints keep requesting the same counts, sums, and rankings.<\/li>\n\n\n\n
- Under write load, those queries become expensive.<\/li>\n<\/ul>\n\n\n\n\n\n\n\n
The usual workaround is a combination of caches, helper tables, or manually maintained materialized-view-like pipelines. It can work, but it adds operational complexity: refresh jobs, stale-data risk, and extra application logic.<\/p>\n\n\n\n
MemCP takes a different path: it does not materialize full grouped result tables by default. Instead, it materializes only what is needed, at the aggregate-column level.<\/p>\n\n\n\n
What Is Different?<\/h2>\n\n\n\n
Instead of storing one full cached result table per grouped query, MemCP separates:<\/p>\n\n\n\n
\n- Group keys (
GROUP BY<\/code> values)<\/li>\n\n\n\n- Aggregate columns (
COUNT(*)<\/code>, SUM(...)<\/code>, and similar expressions)<\/li>\n<\/ol>\n\n\n\nThis allows the engine to cache, invalidate, and recompute much more selectively.<\/p>\n\n\n\n
For application teams, that means:<\/p>\n\n\n\n
\n- no manual materialized-view management for common aggregation workloads<\/li>\n\n\n\n
- less repeated compute for frequently requested grouped metrics<\/li>\n\n\n\n
- more stable latency for dashboards and reporting APIs<\/li>\n<\/ul>\n\n\n\n
A Typical MySQL Scenario<\/h2>\n\n\n\nSELECT department, SUM(salary), COUNT(*)\nFROM employees\nGROUP BY department;<\/code><\/pre>\n\n\n\nIn many production systems, this query (or close variants) is executed over and over, even though only a small subset of rows changed since the previous run.<\/p>\n\n\n\n
MemCP keeps a compact internal key domain (for example, one row per department<\/code>) and attaches aggregate columns to that domain. If a query only needs COUNT(*)<\/code>, the engine does not need to recompute unrelated aggregates just to serve that request.<\/p>\n\n\n\nWhy This Matters in Real Apps<\/h2>\n\n\n\n1) Lower overhead than full materialization<\/h3>\n\n\n\n
Traditional materialized-view workflows are often all-or-nothing: rebuild large result sets or manage refresh logic manually.<\/p>\n\n\n\n
MemCP can work per aggregate column, which reduces unnecessary compute and memory pressure in common analytics paths.<\/p>\n\n\n\n
2) Fine-grained maintenance<\/h3>\n\n\n\n
Most writes affect only a small number of groups.<\/p>\n\n\n\n
MemCP updates or invalidates only affected groups and affected aggregate columns. For additive metrics like SUM<\/code> and COUNT<\/code>, maintenance can be especially cheap.<\/p>\n\n\n\n3) Cross-query reuse<\/h3>\n\n\n\n
If multiple endpoints rely on the same grouped metrics, MemCP can reuse those computed aggregates internally instead of recomputing from scratch for every query.<\/p>\n\n\n\n
This is useful for:<\/p>\n\n\n\n
\n- dashboard tiles<\/li>\n\n\n\n
- KPI endpoints<\/li>\n\n\n\n
- repeated reporting queries<\/li>\n<\/ul>\n\n\n\n
4) Less application-side infrastructure<\/h3>\n\n\n\n
You do not need to build and maintain as much custom cache\/refresh plumbing in your app code just to keep grouped queries fast.<\/p>\n\n\n\n
What MySQL Users Gain<\/h2>\n\n\n\n
Moving from MySQL to MemCP keeps SQL workflows familiar, but changes how aggregation is executed internally:<\/p>\n\n\n\n
\n- repeated
GROUP BY<\/code> queries become cheaper<\/li>\n\n\n\n- mixed read\/write workloads are easier to keep responsive<\/li>\n\n\n\n
- operational burden around aggregation caching is reduced<\/li>\n<\/ul>\n\n\n\n
This is most valuable when your team is already spending time optimizing repeated analytical queries in application code.<\/p>\n\n\n\n
Best Fit Workloads<\/h2>\n\n\n\n\n- SaaS products with many metric views<\/li>\n\n\n\n
- admin backends with heavily used overview pages<\/li>\n\n\n\n
- product analytics with recurring grouped summaries<\/li>\n\n\n\n
- systems that serve reports while ingesting ongoing writes<\/li>\n<\/ul>\n\n\n\n
Bottom Line<\/h2>\n\n\n\n
For teams coming from MySQL, the core advantage is simple:<\/p>\n\n\n\n
MemCP treats aggregations as reusable, independently maintained aggregate columns over group keys, rather than as disposable full-query recomputation or manually maintained full materialized views.<\/p>\n\n\n\n
That improves performance where many apps struggle most: frequent GROUP BY<\/code> queries under concurrent write load.<\/p>\n\n\n\nSource code: https:\/\/github.com\/launix-de\/memcp<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"If you run a MySQL-backed application, this pattern is probably familiar:<\/p>\n","protected":false},"author":2,"featured_media":8162,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","footnotes":""},"categories":[129],"tags":[],"class_list":["post-8161","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-memcp","single-item"],"featured_image_urls_v2":{"full":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b.png",1536,1024,false],"thumbnail":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-150x150.png",150,150,true],"medium":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-300x200.png",300,200,true],"medium_large":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-768x512.png",751,501,true],"large":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-1024x683.png",751,501,true],"1536x1536":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b.png",1536,1024,false],"2048x2048":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b.png",1536,1024,false],"trp-custom-language-flag":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-18x12.png",18,12,true],"xs-thumb":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-64x64.png",64,64,true],"appku-shop-single":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-620x500.png",620,500,true]},"post_excerpt_stackable_v2":"
If you run a MySQL-backed application, this pattern is probably familiar: Dashboards repeatedly execute the same GROUP BY queries. API endpoints keep requesting the same counts, sums, and rankings. Under write load, those queries become expensive. The usual workaround is a combination of caches, helper tables, or manually maintained materialized-view-like pipelines. It can work, but it adds operational complexity: refresh jobs, stale-data risk, and extra application logic. MemCP takes a different path: it does not materialize full grouped result tables by default. Instead, it materializes only what is needed, at the aggregate-column level. What Is Different? Instead of storing one…<\/p>\n","category_list_v2":"MemCP<\/a>","author_info_v2":{"name":"Carl-Philip H\u00e4nsch","url":"https:\/\/launix.de\/launix\/author\/carli\/"},"comments_num_v2":"0 comments","uagb_featured_image_src":{"full":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b.png",1536,1024,false],"thumbnail":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-150x150.png",150,150,true],"medium":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-300x200.png",300,200,true],"medium_large":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-768x512.png",751,501,true],"large":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-1024x683.png",751,501,true],"1536x1536":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b.png",1536,1024,false],"2048x2048":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b.png",1536,1024,false],"trp-custom-language-flag":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-18x12.png",18,12,true],"xs-thumb":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-64x64.png",64,64,true],"appku-shop-single":["https:\/\/launix.de\/launix\/wp-content\/uploads\/2026\/03\/80d735c3-1b4f-4e22-87ef-74218a05560b-620x500.png",620,500,true]},"uagb_author_info":{"display_name":"Carl-Philip H\u00e4nsch","author_link":"https:\/\/launix.de\/launix\/author\/carli\/"},"uagb_comment_info":0,"uagb_excerpt":"If you run a MySQL-backed application, this pattern is probably familiar:","_links":{"self":[{"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/posts\/8161","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/comments?post=8161"}],"version-history":[{"count":1,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/posts\/8161\/revisions"}],"predecessor-version":[{"id":8163,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/posts\/8161\/revisions\/8163"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/media\/8162"}],"wp:attachment":[{"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/media?parent=8161"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/categories?post=8161"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/launix.de\/launix\/wp-json\/wp\/v2\/tags?post=8161"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}