[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fQ5AWLT-TjztdovjfEpcAVyMwQQA9iiQ9_fUqSWJ-aQI":3},{"item":4},{"id":5,"idKnowledge":6,"idDomain":7,"idCluster":7,"kindOverride":8,"slug":9,"title":10,"description":11,"bodyMarkdown":12,"bodyHtml":13,"author":14,"date":15,"createdAt":16,"topics":17,"image":23,"hasDownload":24,"fileName":7,"youtubeId":25},"458","F0E3BB1B-96EC-F946-80EC-C0C29D8AE578","","article","filemaker-scripts-optimaliseren-voor-snelheid","FileMaker scripts optimizing for speed","Why slow FileMaker scripts rarely come down to a single cause, and how to measure, prioritize, and optimize step by step without rewriting everything.","An order confirmation that takes eight seconds might not seem like a big problem. Until five employees perform that action dozens of times a day, while customers wait on the phone and the database keeps growing. Sound familiar? Then this article is about exactly that problem: how to make slow FileMaker scripts fast again, without months of rebuilding.\n\nOptimizing FileMaker scripts isn't just about technical speed. It's about fewer interruptions, predictable processes, and a system that can grow without your team having to work around existing limitations.\n\n## Why is my FileMaker script slow?\n\nThe cause rarely lies in a single bad script. In practice, slowness is often the result of a combination of factors:\n\n- unnecessary window refreshes\n- broad or complex relationships\n- repeated searches within a loop\n- calculations that are recalculated instead of stored\n- scripts running on the client when they should run on the server\n\nA focused analysis prevents you from spending time on cosmetic improvements that have little impact on what users actually experience.\n\n## Where do I start: measuring or rewriting?\n\nAlways measure, never rewrite immediately. The fastest route to better performance is first establishing where users are actually waiting. Don't just ask which screen \"feels slow,\" but look at the concrete process. Does it take a long time to open a customer card? Does it get stuck when generating an invoice? Or does the slowness only become visible once many users are working simultaneously?\n\nMap the start and end time for each process. That can temporarily be done in a log table, with script steps for time registration, or via FileMaker Server's log files. When measuring, don't just look at total duration, but also which subscript, search, import, export, or record operation takes the most time. A fifteen-second script, for example, might spend fourteen seconds on a single relationship calculation.\n\nThen look at the circumstances under which the script runs:\n\n- A script that responds smoothly locally can perform very differently over a slow connection or with hosted data.\n- The size of the dataset matters heavily. A solution that works fine with 5,000 records can slow noticeably with 500,000 records.\n\nOptimizing without that context regularly leads to wrong choices — you end up fixing something that isn't the real bottleneck.\n\n### Which processes should I tackle first?\n\nDon't automatically start with the longest script. Priority usually lies with processes that are used frequently, support revenue, or cause errors when employees have to wait too long. Think of order creation, inventory changes, scheduling, invoicing, and synchronization with an accounting package or web shop.\n\nA monthly report that becomes twenty seconds faster but only runs once a month usually has less business value than an order process that becomes two seconds faster for ten users, every day. This weighing keeps the investment practical and defensible to management.\n\n[[IMAGE:left|clock next to a growing database, symbol for increasing slowdown]]\n\n## In what order do I optimize a script?\n\nMany scripts have grown organically. An extra check was added, later a connection with an external service, and then an exception for one specific customer group. Understandable, but it makes the logic unnecessarily complex. First make visible what the script really needs to do, and only then adjust the execution.\n\nCheck whether each step is still necessary. A script that saves a record, opens it again, checks data, and then saves it again might contain redundant actions. The same applies to scripts that loop through different layouts, sort records when the order is irrelevant, or refresh the window after every change.\n\nEspecially limit context switching. Layout changes, window activation, and navigation to related records add extra load in FileMaker. Work where possible with variables, targeted searches, and scripts that clearly indicate which table context they operate in. That makes a script not only faster but also more reliable when used simultaneously by multiple employees.\n\nUse subscript steps consciously. Small, reusable scripts are valuable for maintenance, but a subscript that's called thousands of times within a large loop can cause unnecessary overhead. Sometimes revising the loop is better. Sometimes it's enough to load data into variables in advance instead of retrieving it repeatedly.\n\n### Why is record-by-record processing often the real problem?\n\nA common pattern: a script loops through a found set and searches for related data separately for each record. With a few dozen records, no one notices. With an import or invoicing run of thousands of lines, it becomes a concrete bottleneck — think of a monthly invoicing run that takes three hours instead of ten minutes.\n\nLook at whether you can move those operations to:\n\n1. one targeted search instead of thousands of separate searches\n2. a relationship or summary field\n3. a batch operation\n4. an import to a temporary table instead of creating and enriching records one by one\n\nWhich method works best depends on the validation needed, error handling, and transaction safety. Speed shouldn't mean you lose [control over data quality](https:\u002F\u002Floggix.com\u002Fblog\u002Fhow-to-improve-data-quality-before-automation-or-ai\u002F).\n\nWith complex datasets, ExecuteSQL can be useful for a targeted data query. However, it's not a standard replacement for relationships or a well-built relationship graph. SQL results require extra attention to data types, error handling, and maintainability. Use it when it demonstrably simplifies a targeted query, not as a patch on an unclear data model.\n\n## Could the problem be not in the script, but in the data?\n\nA script is often not the real problem. If the script calls an unstored calculation on a large related dataset, it will remain slow — no matter how neatly the script steps are written. That's why evaluating fields, relationships, and indexing should be standard to optimization.\n\nUnstored calculations are flexible, but FileMaker must recalculate them when requested. That's fine for limited, current information. For values that rarely change and are used often — totals, classifications, statuses that appear in lists and reports — a stored field or a deliberately updated value can be much more efficient.\n\nAlso check whether search fields can be indexed well. A script that regularly searches an unindexed field takes increasingly more time as files grow. Sometimes the solution is a separate search field with a normalized value, for example for item numbers, email addresses, or external references. This prevents scripts from having to perform cumbersome comparisons.\n\nPay attention to the trade-off between storage and currency:\n\n- A **stored total** is fast, but must be reliably updated whenever underlying lines change — that requires clear script logic and sometimes a transaction approach.\n- An **active calculation** is simpler to maintain, but can become too expensive with many simultaneous users.\n\nThe right choice follows from the usage pattern, not from a general preference of the developer.\n\n## Can I move heavy work away from the user and to the server?\n\nYes, and this is often the biggest performance gain you can achieve in one go. When a script performs intensive calculations, imports, document generation, or integrations, that work doesn't need to run on the employee's workstation. With Perform Script on Server (PSoS), FileMaker Server can execute tasks without a user having to wait for every intermediate step.\n\nThat's particularly useful for:\n\n- nightly synchronizations\n- large imports\n- inventory processing\n- building reports\n\nThe user starts a task and later receives a notification or result. This also reduces the load on the local client and limits the impact of network slowdown.\n\nServer-side scripting does require a different design approach. Script steps that depend on an active window, a layout context, or user interaction behave differently on the server, or simply don't work there. Parameters, error messages, and progress must therefore be explicitly recorded. With [API connections](https:\u002F\u002Floggix.com\u002Fblog\u002Fapi-koppeling-bedrijfssoftware-maken-zonder-omwegen\u002F), it's wise to log requests, catch time-outs, and handle retryable errors in a controlled manner.\n\nFor critical processes — posting an invoice, processing inventory — a transaction is often prudent. This prevents some records from being updated while a next step fails. The benefit lies not only in more consistent data, but also in easier recovery when an external API is temporarily unavailable.\n\n[[IMAGE:right|client and server, with heavy task shifting from client to server]]\n\n## How do I ensure a faster script remains maintainable?\n\nPerformance work becomes fragile when only the original developer understands why a particular step exists. Give scripts functional names therefore, group logical blocks, and document exceptions briefly but concretely. A note like \"made faster\" helps no one. \"Prevents repeated search per order line during import\" makes the choice immediately understandable to the next developer — even if that's yourself a year later.\n\n[Build error handling in](https:\u002F\u002Floggix.com\u002Fblog\u002Fwhy-exception-handling-determines-process-efficiency\u002F) at the places where risk exists:\n\n- record locks\n- missing related records\n- failed API calls\n- invalid input\n\nThen verify the result of important script steps. A faster script that silently skips data creates a much costlier problem later than the original wait time ever was.\n\nUse a separate test environment when processes are business-critical. Test not only the happy path, but also large datasets, missing data, concurrent changes, and a temporary disruption in a connection. In existing FileMaker environments, that discipline is essential, because scripts are often intertwined with years of business rules that no one can fully recount anymore.\n\n## Checklist: Optimizing FileMaker scripts in practice\n\n1. Measure which process actually feels slow — ask questions until you reach the screen and the action.\n2. Log start and end time per script and per subscript.\n3. Look at data volume and network circumstances, not just the script code.\n4. Choose processes with business impact, not automatically the longest script.\n5. Remove unnecessary script steps and unnecessary layout switches.\n6. Replace record-by-record processing with searches, relationships, or batch processing where possible.\n7. Check unstored calculations and indexing of frequently used search fields.\n8. Move heavy tasks to FileMaker Server via Perform Script on Server.\n9. Build transactions and error handling into critical processes.\n10. Document changes functionally, not cosmetically.\n11. Test with realistic data volumes and failure scenarios, not just the happy path.\n\n## Frequently asked questions\n\n**Is ExecuteSQL always faster than relationships?**\nNot necessarily. ExecuteSQL can simplify a targeted, complex query, but doesn't replace a well-built data model. Use it deliberately, not as a standard solution.\n\n**Do I need to store all calculations for better speed?**\nNo. Stored calculations are faster when retrieved, but require reliable update logic. For values that are rarely queried, an unstored calculation is often simpler and equally practical.\n\n**Does Perform Script on Server work for every script?**\nNo. Scripts that depend on an active window or direct user interaction need to be revised before they can run server-side.\n\n**How often should I review scripts for speed?**\nWhenever there's noticeable growth in user numbers or data volume, and certainly whenever there are complaints about specific processes. A quick yearly performance check prevents small slowdowns from quietly piling up.\n\n## What is the best next step?\n\nA good first step is a short performance audit of the most important processes. Then choose one or two improvements that are immediately noticeable to users, for example a faster order process or an invoicing run that runs on the server. Measure the result and use those insights for the next priority.\n\nSometimes cleaning up scripts and fields is enough. Sometimes the analysis reveals a broader problem, such as outdated FileMaker Server configuration, an unclear relationship graph, or an integration that sends too many loose requests. Then modernizing a subprocess is wiser than endless repairs.\n\nThe best improvement is ultimately not the technically smartest solution on paper, but the solution that allows employees to complete their work without waiting, detours, or uncertainty.\n\nLoggix takes a first look at this type of project at what already works well, and searches deliberately for the places where speed delivers direct business value — whether that's in restructuring existing FileMaker scripts, moving heavy processing to the server, tightening an API connection with an external system, or taking a broader look at where the current data model constrains your organization's growth. A focused performance audit is often the fastest way to discover where that value lies for your specific processes.","\u003Cp>An order confirmation that takes eight seconds might not seem like a big problem. Until five employees perform that action dozens of times a day, while customers wait on the phone and the database keeps growing. Sound familiar? Then this article is about exactly that problem: how to make slow FileMaker scripts fast again, without months of rebuilding.\u003C\u002Fp>\n\u003Cp>Optimizing FileMaker scripts isn't just about technical speed. It's about fewer interruptions, predictable processes, and a system that can grow without your team having to work around existing limitations.\u003C\u002Fp>\n\u003Ch2>Why is my FileMaker script slow?\u003C\u002Fh2>\n\u003Cp>The cause rarely lies in a single bad script. In practice, slowness is often the result of a combination of factors:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>unnecessary window refreshes\u003C\u002Fli>\n\u003Cli>broad or complex relationships\u003C\u002Fli>\n\u003Cli>repeated searches within a loop\u003C\u002Fli>\n\u003Cli>calculations that are recalculated instead of stored\u003C\u002Fli>\n\u003Cli>scripts running on the client when they should run on the server\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>A focused analysis prevents you from spending time on cosmetic improvements that have little impact on what users actually experience.\u003C\u002Fp>\n\u003Ch2>Where do I start: measuring or rewriting?\u003C\u002Fh2>\n\u003Cp>Always measure, never rewrite immediately. The fastest route to better performance is first establishing where users are actually waiting. Don't just ask which screen "feels slow," but look at the concrete process. Does it take a long time to open a customer card? Does it get stuck when generating an invoice? Or does the slowness only become visible once many users are working simultaneously?\u003C\u002Fp>\n\u003Cp>Map the start and end time for each process. That can temporarily be done in a log table, with script steps for time registration, or via FileMaker Server's log files. When measuring, don't just look at total duration, but also which subscript, search, import, export, or record operation takes the most time. A fifteen-second script, for example, might spend fourteen seconds on a single relationship calculation.\u003C\u002Fp>\n\u003Cp>Then look at the circumstances under which the script runs:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>A script that responds smoothly locally can perform very differently over a slow connection or with hosted data.\u003C\u002Fli>\n\u003Cli>The size of the dataset matters heavily. A solution that works fine with 5,000 records can slow noticeably with 500,000 records.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Optimizing without that context regularly leads to wrong choices — you end up fixing something that isn't the real bottleneck.\u003C\u002Fp>\n\u003Ch3>Which processes should I tackle first?\u003C\u002Fh3>\n\u003Cp>Don't automatically start with the longest script. Priority usually lies with processes that are used frequently, support revenue, or cause errors when employees have to wait too long. Think of order creation, inventory changes, scheduling, invoicing, and synchronization with an accounting package or web shop.\u003C\u002Fp>\n\u003Cp>A monthly report that becomes twenty seconds faster but only runs once a month usually has less business value than an order process that becomes two seconds faster for ten users, every day. This weighing keeps the investment practical and defensible to management.\u003C\u002Fp>\n\u003Cp>[[IMAGE:left|clock next to a growing database, symbol for increasing slowdown]]\u003C\u002Fp>\n\u003Ch2>In what order do I optimize a script?\u003C\u002Fh2>\n\u003Cp>Many scripts have grown organically. An extra check was added, later a connection with an external service, and then an exception for one specific customer group. Understandable, but it makes the logic unnecessarily complex. First make visible what the script really needs to do, and only then adjust the execution.\u003C\u002Fp>\n\u003Cp>Check whether each step is still necessary. A script that saves a record, opens it again, checks data, and then saves it again might contain redundant actions. The same applies to scripts that loop through different layouts, sort records when the order is irrelevant, or refresh the window after every change.\u003C\u002Fp>\n\u003Cp>Especially limit context switching. Layout changes, window activation, and navigation to related records add extra load in FileMaker. Work where possible with variables, targeted searches, and scripts that clearly indicate which table context they operate in. That makes a script not only faster but also more reliable when used simultaneously by multiple employees.\u003C\u002Fp>\n\u003Cp>Use subscript steps consciously. Small, reusable scripts are valuable for maintenance, but a subscript that's called thousands of times within a large loop can cause unnecessary overhead. Sometimes revising the loop is better. Sometimes it's enough to load data into variables in advance instead of retrieving it repeatedly.\u003C\u002Fp>\n\u003Ch3>Why is record-by-record processing often the real problem?\u003C\u002Fh3>\n\u003Cp>A common pattern: a script loops through a found set and searches for related data separately for each record. With a few dozen records, no one notices. With an import or invoicing run of thousands of lines, it becomes a concrete bottleneck — think of a monthly invoicing run that takes three hours instead of ten minutes.\u003C\u002Fp>\n\u003Cp>Look at whether you can move those operations to:\u003C\u002Fp>\n\u003Col>\n\u003Cli>one targeted search instead of thousands of separate searches\u003C\u002Fli>\n\u003Cli>a relationship or summary field\u003C\u002Fli>\n\u003Cli>a batch operation\u003C\u002Fli>\n\u003Cli>an import to a temporary table instead of creating and enriching records one by one\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Cp>Which method works best depends on the validation needed, error handling, and transaction safety. Speed shouldn't mean you lose \u003Ca href=\"https:\u002F\u002Floggix.com\u002Fblog\u002Fhow-to-improve-data-quality-before-automation-or-ai\u002F\">control over data quality\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>With complex datasets, ExecuteSQL can be useful for a targeted data query. However, it's not a standard replacement for relationships or a well-built relationship graph. SQL results require extra attention to data types, error handling, and maintainability. Use it when it demonstrably simplifies a targeted query, not as a patch on an unclear data model.\u003C\u002Fp>\n\u003Ch2>Could the problem be not in the script, but in the data?\u003C\u002Fh2>\n\u003Cp>A script is often not the real problem. If the script calls an unstored calculation on a large related dataset, it will remain slow — no matter how neatly the script steps are written. That's why evaluating fields, relationships, and indexing should be standard to optimization.\u003C\u002Fp>\n\u003Cp>Unstored calculations are flexible, but FileMaker must recalculate them when requested. That's fine for limited, current information. For values that rarely change and are used often — totals, classifications, statuses that appear in lists and reports — a stored field or a deliberately updated value can be much more efficient.\u003C\u002Fp>\n\u003Cp>Also check whether search fields can be indexed well. A script that regularly searches an unindexed field takes increasingly more time as files grow. Sometimes the solution is a separate search field with a normalized value, for example for item numbers, email addresses, or external references. This prevents scripts from having to perform cumbersome comparisons.\u003C\u002Fp>\n\u003Cp>Pay attention to the trade-off between storage and currency:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>A \u003Cstrong>stored total\u003C\u002Fstrong> is fast, but must be reliably updated whenever underlying lines change — that requires clear script logic and sometimes a transaction approach.\u003C\u002Fli>\n\u003Cli>An \u003Cstrong>active calculation\u003C\u002Fstrong> is simpler to maintain, but can become too expensive with many simultaneous users.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>The right choice follows from the usage pattern, not from a general preference of the developer.\u003C\u002Fp>\n\u003Ch2>Can I move heavy work away from the user and to the server?\u003C\u002Fh2>\n\u003Cp>Yes, and this is often the biggest performance gain you can achieve in one go. When a script performs intensive calculations, imports, document generation, or integrations, that work doesn't need to run on the employee's workstation. With Perform Script on Server (PSoS), FileMaker Server can execute tasks without a user having to wait for every intermediate step.\u003C\u002Fp>\n\u003Cp>That's particularly useful for:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>nightly synchronizations\u003C\u002Fli>\n\u003Cli>large imports\u003C\u002Fli>\n\u003Cli>inventory processing\u003C\u002Fli>\n\u003Cli>building reports\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>The user starts a task and later receives a notification or result. This also reduces the load on the local client and limits the impact of network slowdown.\u003C\u002Fp>\n\u003Cp>Server-side scripting does require a different design approach. Script steps that depend on an active window, a layout context, or user interaction behave differently on the server, or simply don't work there. Parameters, error messages, and progress must therefore be explicitly recorded. With \u003Ca href=\"https:\u002F\u002Floggix.com\u002Fblog\u002Fapi-koppeling-bedrijfssoftware-maken-zonder-omwegen\u002F\">API connections\u003C\u002Fa>, it's wise to log requests, catch time-outs, and handle retryable errors in a controlled manner.\u003C\u002Fp>\n\u003Cp>For critical processes — posting an invoice, processing inventory — a transaction is often prudent. This prevents some records from being updated while a next step fails. The benefit lies not only in more consistent data, but also in easier recovery when an external API is temporarily unavailable.\u003C\u002Fp>\n\u003Cp>[[IMAGE:right|client and server, with heavy task shifting from client to server]]\u003C\u002Fp>\n\u003Ch2>How do I ensure a faster script remains maintainable?\u003C\u002Fh2>\n\u003Cp>Performance work becomes fragile when only the original developer understands why a particular step exists. Give scripts functional names therefore, group logical blocks, and document exceptions briefly but concretely. A note like "made faster" helps no one. "Prevents repeated search per order line during import" makes the choice immediately understandable to the next developer — even if that's yourself a year later.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Floggix.com\u002Fblog\u002Fwhy-exception-handling-determines-process-efficiency\u002F\">Build error handling in\u003C\u002Fa> at the places where risk exists:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>record locks\u003C\u002Fli>\n\u003Cli>missing related records\u003C\u002Fli>\n\u003Cli>failed API calls\u003C\u002Fli>\n\u003Cli>invalid input\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Then verify the result of important script steps. A faster script that silently skips data creates a much costlier problem later than the original wait time ever was.\u003C\u002Fp>\n\u003Cp>Use a separate test environment when processes are business-critical. Test not only the happy path, but also large datasets, missing data, concurrent changes, and a temporary disruption in a connection. In existing FileMaker environments, that discipline is essential, because scripts are often intertwined with years of business rules that no one can fully recount anymore.\u003C\u002Fp>\n\u003Ch2>Checklist: Optimizing FileMaker scripts in practice\u003C\u002Fh2>\n\u003Col>\n\u003Cli>Measure which process actually feels slow — ask questions until you reach the screen and the action.\u003C\u002Fli>\n\u003Cli>Log start and end time per script and per subscript.\u003C\u002Fli>\n\u003Cli>Look at data volume and network circumstances, not just the script code.\u003C\u002Fli>\n\u003Cli>Choose processes with business impact, not automatically the longest script.\u003C\u002Fli>\n\u003Cli>Remove unnecessary script steps and unnecessary layout switches.\u003C\u002Fli>\n\u003Cli>Replace record-by-record processing with searches, relationships, or batch processing where possible.\u003C\u002Fli>\n\u003Cli>Check unstored calculations and indexing of frequently used search fields.\u003C\u002Fli>\n\u003Cli>Move heavy tasks to FileMaker Server via Perform Script on Server.\u003C\u002Fli>\n\u003Cli>Build transactions and error handling into critical processes.\u003C\u002Fli>\n\u003Cli>Document changes functionally, not cosmetically.\u003C\u002Fli>\n\u003Cli>Test with realistic data volumes and failure scenarios, not just the happy path.\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch2>Frequently asked questions\u003C\u002Fh2>\n\u003Cp>\u003Cstrong>Is ExecuteSQL always faster than relationships?\u003C\u002Fstrong>\nNot necessarily. ExecuteSQL can simplify a targeted, complex query, but doesn't replace a well-built data model. Use it deliberately, not as a standard solution.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Do I need to store all calculations for better speed?\u003C\u002Fstrong>\nNo. Stored calculations are faster when retrieved, but require reliable update logic. For values that are rarely queried, an unstored calculation is often simpler and equally practical.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Does Perform Script on Server work for every script?\u003C\u002Fstrong>\nNo. Scripts that depend on an active window or direct user interaction need to be revised before they can run server-side.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>How often should I review scripts for speed?\u003C\u002Fstrong>\nWhenever there's noticeable growth in user numbers or data volume, and certainly whenever there are complaints about specific processes. A quick yearly performance check prevents small slowdowns from quietly piling up.\u003C\u002Fp>\n\u003Ch2>What is the best next step?\u003C\u002Fh2>\n\u003Cp>A good first step is a short performance audit of the most important processes. Then choose one or two improvements that are immediately noticeable to users, for example a faster order process or an invoicing run that runs on the server. Measure the result and use those insights for the next priority.\u003C\u002Fp>\n\u003Cp>Sometimes cleaning up scripts and fields is enough. Sometimes the analysis reveals a broader problem, such as outdated FileMaker Server configuration, an unclear relationship graph, or an integration that sends too many loose requests. Then modernizing a subprocess is wiser than endless repairs.\u003C\u002Fp>\n\u003Cp>The best improvement is ultimately not the technically smartest solution on paper, but the solution that allows employees to complete their work without waiting, detours, or uncertainty.\u003C\u002Fp>\n\u003Cp>Loggix takes a first look at this type of project at what already works well, and searches deliberately for the places where speed delivers direct business value — whether that's in restructuring existing FileMaker scripts, moving heavy processing to the server, tightening an API connection with an external system, or taking a broader look at where the current data model constrains your organization's growth. A focused performance audit is often the fastest way to discover where that value lies for your specific processes.\u003C\u002Fp>\n","Jeroen","2026-08-03",1785757914000,[18,19,20,21,22],"FileMaker","performance optimalisatie","scripting","FileMaker Server","maatwerksoftware","\u002Fapi\u002Fknowledge\u002Fimage\u002F458\u002F?v=d20f809d223b",false,null]