Speaker 1: You've heard this phrase before, casually dropped into Microsoft teams
Speaker 1: calls with frightening confidence. Oh, we'll just use SharePoint as
Speaker 1: the database for our power app. And there it is
Speaker 1: the modern cry of the over confidence citizen developer. This
Speaker 1: right here is the problem. People here at data stored
Speaker 1: somewhere and immediately conclude database. By that logic, your junk
Speaker 1: draw is a supply chain management system. The confusion is
Speaker 1: forgivable barely. SharePoint does hold data and power apps can
Speaker 1: read it, but that does not make it a database
Speaker 1: anymore than Excel becomes a server when you save two worksheets.
Speaker 1: Average users love the illusion. SharePoint lists look structured. They
Speaker 1: have columns and rows, fields and filters, and of course
Speaker 1: it's already included in Microsoft three sixty five, so it
Speaker 1: must be good enough. Right. Wrong. You're about to see
Speaker 1: why the free database sitting in your tenant is a
Speaker 1: performance time bomb disguised as convenience. By the end, you'll
Speaker 1: understand why power apps that begin with just SharePoint eventually
Speaker 1: die gasping under their own weight, and why treating it
Speaker 1: like sickle is the digital equivalent of trusting a filing
Speaker 1: cabinet to run an engine. What a database actually is.
Speaker 1: Let's reset the definitions before your app implodes. A proper
Speaker 1: database isn't just a bucket that holds information. It's a
Speaker 1: system built on architecture and logic. It has order, schema, indexing, relationships,
Speaker 1: and concurrency control the invisible infrastructure that leads dozens or
Speaker 1: thousands of users read, write, and query your data without
Speaker 1: tripping over each other. Sequel server and data verse handle
Speaker 1: this beautifully. Skimmers define the blueprint, every column type and
Speaker 1: constraint serves like support beams in a skyscraper. Indexes act
Speaker 1: as the elevator shafts that get you exactly where you need.
Speaker 1: Fast relationships, keep records consistent, ensuring that when one table sneezes,
Speaker 1: its related tables say bless you in perfect synchronization. Now
Speaker 1: compare that to SharePoint. SharePoint was not designed to manage
Speaker 1: transactions at scale. Its DNA is collaboration, version, history, permissions,
Speaker 1: and file storage. It's more like a glorified document librarian
Speaker 1: than a record keeping accountant. It's wonderful at organizing text,
Speaker 1: attachments and metadata. But call it a database and you
Speaker 1: might as well call your filing cabinet a data processing engine.
Speaker 1: Real databases think in joints, rev rntial integrity and execution plans.
Speaker 1: SharePoint thinks in lists, permissions, and column choices written by
Speaker 1: someone who definitely didn't study relational theory. It's a web
Speaker 1: layer optimized for people, not for queries. Here's where the
Speaker 1: power apps confusion begins. The app happily connects to SharePoint
Speaker 1: through an data connector. You can create forms, galleries, and dashboards.
Speaker 1: On the surface, everything looks professional. The danger is invisible
Speaker 1: until your app grows. I once met a department that
Speaker 1: proudly built their internal CRM entirely on top of four
Speaker 1: SharePoint lists. It worked beautifully for a month, then came
Speaker 1: the fifth thousand record. Suddenly the apps stuttered, screens froze,
Speaker 1: and every gallery took half a minute to load. Their
Speaker 1: users thought the problem was bad Wi Fi. It wasn't
Speaker 1: Wi fi, it was physics. SharePoint was trying to impersonate
Speaker 1: a relational database. The truth. Power apps can connect to SharePoint,
Speaker 1: but that's all it does. Connect. It borrows the data source,
Speaker 1: but it doesn't make SharePoint any smarter. There's no hidden
Speaker 1: engine under the surface waiting to optimize your queries. Imagine
Speaker 1: trying to raise with a car built from bicycle parts.
Speaker 1: Sure it has wheels, it moves, but once you hit
Speaker 1: highway speeds, bolts start flying the handlebars. The list structure
Speaker 1: where never designed to steer that kind of load. Data Verse,
Speaker 1: in contrast, is a proper engine. Its transactional, relational, optimized
Speaker 1: for delegation and built for power platform from the ground up.
Speaker 1: It follows database logic, not just storage logic. That's the
Speaker 1: difference between structured speed and unstructured sprawl. SharePoint has indexing,
Speaker 1: but limited. It has look up columns, but no genuine
Speaker 1: referential constraints. It allows multiple users, but not graceful concurrency handling.
Speaker 1: You can write to it, but if three users added
Speaker 1: the same record at once, one loses usually the intern Essentially,
Speaker 1: a database enforces integrity. While SharePoint hopes for good behavior,
Speaker 1: Circle refuses to accept invalid relationships. SharePoint accepts everything, smiles politely,
Speaker 1: and breaks quietly. Months later. If this still feels theoretical,
Speaker 1: don't worry. Scale will make it painfully real, because while
Speaker 1: architecture can be ignored for a while, performance cannot, and
Speaker 1: as your user base grows, your database made from friendly
Speaker 1: SharePoint lists will groan like a spreadsheet with delusions of grandeur.
Speaker 1: The next part is where the collapse begins. Microsoft's shiny
Speaker 1: number thirty million items and the cruel joke hiding behind it.
Speaker 1: Let's talk about scale, the silent killer of every power
Speaker 1: app that mistook convenience for capability, the scale myth. Microsoft
Speaker 1: loves big numbers. Nothing sells confidence like a glossy documentation
Speaker 1: page claiming your share Point list can hold wait for it,
Speaker 1: thirty million items sounds impressive, doesn't it. Thirty million entries
Speaker 1: you could store the payroll history of an empire. But
Speaker 1: the problem is that the number is marketing, not math.
Speaker 1: That limit describes what share Point can physically contain, not
Speaker 1: what it can functionally handle. It's like saying a washing
Speaker 1: machine can technically fit ten bowling balls. True until you
Speaker 1: press start. In reality, the moment those lists creep beyond
Speaker 1: a few thousand records, power apps begins its slow descent
Speaker 1: into misery. Buttons take seconds to respond. Galleries forget how
Speaker 1: to scroll smoothly. You click filter and the spinning dots
Speaker 1: start an existential performance art piece by ten thousand records.
Speaker 1: It feels like wading through syrup. Beyond that, you're practically
Speaker 1: time traveling all the way back to dial up. The
Speaker 1: core culprit here is a polite little concept called delegation.
Speaker 1: It's power App's way of saying, I can't handle that
Speaker 1: query locally, so I'll ask the data source to compute
Speaker 1: it for me. SharePoint, however, isn't fluent in that language.
Speaker 1: Its delegation capabilities are minimal. Translation anything outside a small
Speaker 1: set of filter and sought operations is pulled locally. The
Speaker 1: data comes down the wire record by records, so your
Speaker 1: client device ends up doing the heavy lifting a real
Speaker 1: database engine would have done in milliseconds. You built an
Speaker 1: enterprise app, and now every user's laptop is its database server. Congratulations.
Speaker 1: The infamous two thousand item delegation wall isn't a myth.
Speaker 1: It's a design constraint. Unless you use creative and usually
Speaker 1: fragile pagination workarounds, power App simply refuses to process more.
Speaker 1: You can raise that ceiling a little with clever queries,
Speaker 1: but eventually the data set expands faster than the platform
Speaker 1: can pretend nothing's wrong. Even if you index your columns
Speaker 1: the supposed magic trick, things only improve marginally, like upgrading
Speaker 1: a rubber band with a thicker rubber band. Microsoft's documentation
Speaker 1: hints that indexing can let you manage up to around
Speaker 1: twenty five thousand records if you're careful. Translation it will
Speaker 1: technically work while producing the user experience of a PowerPoint
Speaker 1: slide show transmitted over carrier pigeons. The indexes prevent total collapse,
Speaker 1: but can't change the fact that SharePoint stores data in
Speaker 1: what is essentially a flattened web table. Each query becomes
Speaker 1: a request for a giant Jason blob passed piece by piece,
Speaker 1: squirrel or data verse by contrast sends back neat pre
Speaker 1: processed chunks of matching rows. SharePoint just hands you everything
Speaker 1: and says good luck sorting it. Every extra thousand records
Speaker 1: adds latency. It's not linear, it's exponential. One thousand rows acceptable,
Speaker 1: ten thousand noticeable lag twenty thousand. Every gallery becomes a
Speaker 1: meditation exercise. Users start clicking twice, thinking their devices froze,
Speaker 1: which of course triggers double updates and conflicting rights. That's
Speaker 1: when someone suggests, maybe we should rebuild this in Excel,
Speaker 1: and the circle of bad decisions completes itself. Using SharePoint
Speaker 1: as a back end at scale is like powering a
Speaker 1: data center with AA batteries. Each small operation works barely,
Speaker 1: but time and concurrency amplify the load until the whole
Speaker 1: thing starts coughing the connect Try to fetch data while
Speaker 1: maintaining security, context, evaluating filters, and managing throttling all over
Speaker 1: cloud http calls that multiply faster than your patients decreases. Meanwhile,
Speaker 1: Data Verse or SQUAL would be compressing, caching, and delegating
Speaker 1: queries Natively. Share Points response to that level of complexity
Speaker 1: a polite shrug followed by a timeout, and don't forget
Speaker 1: throttling once you exceed certain thresholds. In Office three sixty five,
Speaker 1: Sharepoints starts limiting the number of requests per user per minute.
Speaker 1: It doesn't warn you nicely, it simply refuses to serve
Speaker 1: data for a few seconds. Multiply that delay by hundreds
Speaker 1: of active users, and you've turned your business app into
Speaker 1: a queue simulator. Remember, throttling isn't failure. It's share points
Speaker 1: polite way of begging you to stop abusing it. Now,
Speaker 1: let's add relationships into the mix. Many creators think scaling
Speaker 1: problems vanish if they just break lists apart. We'll have
Speaker 1: one for customers, one for orders, one for products and
Speaker 1: link them fascinating optimism. Each look up between those lists
Speaker 1: triggers its own set of API calls, So when you
Speaker 1: open a single record, you're actually launching dozens of hidden queries.
Speaker 1: Apply that by hundreds of users, and your app starts
Speaker 1: behaving like a chainsmoker climbing stairs. Power apps will valiantly
Speaker 1: try to batch requests, but latency stacks faster than performance
Speaker 1: optimizers can patch it. What's particularly cruel is how invisible
Speaker 1: the decay feels. At first. Everything seems fine until the
Speaker 1: day new data pushes you past that unseen tipping point.
Speaker 1: Then screens freeze, connections fail silently. Eventually, developers start layering
Speaker 1: patchwork fixes, smaller galleries, manual catching, collection tricks to load
Speaker 1: subsets of data. It looks like progress, but only delays
Speaker 1: the inevitable. It's like rearranging deck chairs on a server
Speaker 1: farm that's on fire. People mistake reliability for survival time.
Speaker 1: It's worked for months, they say, proudly, ignoring the trend line.
Speaker 1: A proper database scales predictably. More data means slightly more storage,
Speaker 1: not exponentially slower queries, SharePoint scales emotionally. It starts healthy.
Speaker 1: Then suddenly collapses like it just remembered it's a web
Speaker 1: service from two thousand and three, and yet the illusion persists.
Speaker 1: Because Microsoft includes SharePoint in the license, the tool is approachable,
Speaker 1: the set up effortless, and the first prototype thrillingly quick,
Speaker 1: but free convenience hides catastrophic economics. Each delay compounds across users, departments,
Speaker 1: and workflows until productivity losses dwarf any licensing savings. The
Speaker 1: irony the organization eventually pays far more for an included
Speaker 1: feature than it would have for data versus so called
Speaker 1: premium price. You wanted relational joints across lists fascinating, Do
Speaker 1: you also expect teleportation because that's about as plausible Inside
Speaker 1: Sharepoints architecture, the list interface wasn't built for transactional queries
Speaker 1: or complex aggregation. It's a collaborative document store that's being
Speaker 1: forced daily to impersonate a relational database. No wonder it
Speaker 1: looks tired. So the next time someone quotes that thirty
Speaker 1: million item limit, pause, ask them how many they've actually
Speaker 1: queried successfully in power apps without freezing the app. The
Speaker 1: number will be much smaller, somewhere between few thousand and
Speaker 1: Please don't ask. That's not scale. That's tolerance, and tolerance
Speaker 1: runs out. What follows it is the crash every power
Speaker 1: app team eventually experiences the day their free database becomes
Speaker 1: a very expensive bottlenet. The visible slowdown is just the start.
Speaker 1: What comes next is subtler, the kind of corruption hidden
Speaker 1: behind seemingly normal forms and look ups. Because while performance
Speaker 1: pain screams, integrity failure whispers, and in the next section
Speaker 1: those whispers turn into full blown data chaos, relationships, look ups,
Speaker 1: and other dangerous illusions. Now we reach the part where
Speaker 1: SharePoint proudly pretends to be relational. It waives its little
Speaker 1: look up column and declares, c I can do relationships too. No,
Speaker 1: you can't, not the kind that mattered, Not the kind
Speaker 1: with referential integrity, cascading updates, and proper foreign keys. What
Speaker 1: SharePoint offers is a child's drawing of a database scribbled
Speaker 1: in crayon, queued from a far horrifying up close in
Speaker 1: a real database. Relationships are contracts. Table A promises to
Speaker 1: link only to valid records in table B. If you
Speaker 1: delete something in B, the database enforces. What happens next
Speaker 1: either block it, cascaded, or update accordingly. Integrity is law.
Speaker 1: Share Point by contrast, treats relationships as gossip. I heard
Speaker 1: record X, might know record why, but who can say really?
Speaker 1: Delete the parent list item and the child keeps an
Speaker 1: orphaned reference quietly rotting until a user clicks it and
Speaker 1: gets an error that looks like a riddle. Developers cling
Speaker 1: to look up columns thinking they're safe, and they're not relationships.
Speaker 1: They're lightweight pointers that store the ID and a bit
Speaker 1: of display text, nothing more. They don't validate consistency, they
Speaker 1: don't prevent duplicates. They simply assume nothing will go wrong,
Speaker 1: which is adorable. And when power apps uses those lookups,
Speaker 1: it has to perform multiple calls, one to retrieve the
Speaker 1: main list, another to resolve each look up. That's dozens
Speaker 1: of round trips just to reconstruct what cycle would fetch
Speaker 1: in one joint. Every lookup adds lag, every nested gallery
Speaker 1: doubles it. Choice columns are equally misleading. They look like
Speaker 1: constraint enforcement preset options, clean new eye, but under the
Speaker 1: hood their glorified text fields decorated with drop downs. Each
Speaker 1: choice is stored as plain text or sometimes Jason flavored markup,
Speaker 1: depending on column settings. Good luck filtering efficiently data verse
Speaker 1: translates options into integer mapped sets for quick comparison. Share
Speaker 1: Point just sifts through strings the way a librarian searches
Speaker 1: a card catalog in the dark. Then we have the
Speaker 1: illusion of normalization. In legitimate database design, normalization prevents redundancy.
Speaker 1: Each entity lives exactly once, saving space and ensuring consistency.
Speaker 1: Sharepointnds politely and does the opposite. Lists operate in parallel universes.
Speaker 1: You can normalize manually split your data into multiple lists
Speaker 1: and reference them, but every look up slows performance. Normalize
Speaker 1: too much and your power app spends its life resolving
Speaker 1: relationships instead of serving users. Denormalized to simplify performance, and
Speaker 1: you sacrifice integrity, turning your lists into mutant hybrids full
Speaker 1: of duplicated values. It's a loose, lose game designed by
Speaker 1: someone who mistook sheet music for a soundtrack. The practical
Speaker 1: outcome most power apps running on SharePoint settle into lazy denormalization.
Speaker 1: Each list becomes a wide table stuffed with repeating data
Speaker 1: just to avoid fetching lookups. It feels efficient until the
Speaker 1: data starts drifting. Department names, misspelled users, duplicated references out
Speaker 1: of sync. By month three, your database agrees with itself
Speaker 1: about as much as conspiracy theorists at a Flat Earth convention.
Speaker 1: Power Apps compounds this with its handling of data calls.
Speaker 1: Each related record shown in a form is fetched via
Speaker 1: a separate query, occasionally catching masks the inefficiency, but open
Speaker 1: a deep form with multiple look ups, client, product manager status,
Speaker 1: and behind the scenes, SharePoint is juggling a small crowd
Speaker 1: of network requests. Any latency along the way multiplies. The
Speaker 1: result is that users open a record, wait a few seconds,
Speaker 1: then start clicking out of frustration, triggering another round of
Speaker 1: premature network chaos. Developers respond with clever but ruinous workarounds, collections,
Speaker 1: local caches, manual jason passing all in the name of
Speaker 1: pretending relationships behave like secral joints. It works briefly until
Speaker 1: update conflicts appear. Someone edits from a mobile version while
Speaker 1: another user edits the same record in the browser. SharePoint
Speaker 1: doesn't negotiate. It simply overrides. One person wins, the other
Speaker 1: loses silently. The system smiles and tells you everything safe correctly.
Speaker 1: It didn't imagine running a bank ledger on post it notes.
Speaker 1: Each look up column is another sticky label you might misplace.
Speaker 1: At small scale, you can keep track. Once the wind
Speaker 1: picks up, say, concurrent users bulk updates or automated flows.
Speaker 1: The notes scattered. That's SharePoint relationships held together by duct
Speaker 1: tape and hope forever one sneeze away from chaos. Even
Speaker 1: more deceptive is how friendly it feels. At first. The
Speaker 1: interface offers easy linking between lists. You click a drop down,
Speaker 1: pick look up from another list, and instantly it seems powerful.
Speaker 1: But underneath, no relational matter data exists. Just store text
Speaker 1: with a fragile correlation ID, delete or rename the target column,
Speaker 1: and you've broken the map. Power apps tries to follow
Speaker 1: the trail and falls through a logic hole debugging that
Speaker 1: is like tracing spaghetti in a fog. Normalization evangelists eventually
Speaker 1: face an existential crisis. They design beautifully structured SharePoint lists, employees, departments, projects,
Speaker 1: each with crisp lookups. Then they publish the app and
Speaker 1: users complain it's unbearably slow. The architects capitulate, merge lists,
Speaker 1: denormalize data, and accept the compromise. SharePoint rewards disorder, punishing
Speaker 1: proper design. It's the academic equivalent of a teacher docking points.
Speaker 1: For turning in grammar that's too correct by now you
Speaker 1: should see the broader point. SharePoint doesn't understand relational theory
Speaker 1: because it was never meant to. It's built for story documents,
Speaker 1: comments and metadata about those documents, not executing complex relational logic.
Speaker 1: The moment you rely on it to maintain relationships, you're
Speaker 1: forcing a librarian to perform as a database administrator. It smiles,
Speaker 1: pretends to help, then misfiles half your records behind the photocopier,
Speaker 1: and yet people remain hopeful. Maybe security makes up for it,
Speaker 1: they say, as though item level permissions could save structural design. Spoiler,
Speaker 1: they can't. Security may look like order, but when applied
Speaker 1: at sharepoints microscopic scale, it becomes another performance traps. So
Speaker 1: before you declare victory because our lists have look ups,
Speaker 1: pause and check the integrity. If the links break and
Speaker 1: nobody notices until the quarterly report, you've built a time bomb, Quiet,
Speaker 1: polite and waiting. Next, let's test whether security really redeems
Speaker 1: any of this architectural chaos, or if, like the rest,
Speaker 1: it's merely another illusion wrapped in a SharePoint smile security
Speaker 1: life cycle and tag debt ah. Yes, the comfort blanket
Speaker 1: of every SharePoint apologist security. But it has amazing permissions,
Speaker 1: they say, technically true, functionally disastrous. SharePoint does, in fact,
Speaker 1: let you assign security at almost any level imaginable. Side library,
Speaker 1: list item. You can lock down a single row so
Speaker 1: tightly that even its creator can't find it again. It's
Speaker 1: a marvel of granularity. It's also a nightmare of maintainability.
Speaker 1: In a real database like secol or data Verse, security
Speaker 1: operates predictably. You define roles reader, contributor admin. Those roles
Speaker 1: apply at the table, row, or even column level, depending
Speaker 1: on the engine. There's structure, there's logic. The boundaries are
Speaker 1: enforced systematically, not emotionally. SharePoint, however, applies security like confetti
Speaker 1: at a wedding. It's everywhere, and no one remembers who
Speaker 1: threw it. Each time you break inheritance on a list item.
Speaker 1: SharePoint creates an independent access control list entry sounds fine
Speaker 1: until you have hundreds, ten thousands each demanding separate evaluation
Speaker 1: by the permission engine. That's when queries slow down, not
Speaker 1: because your data is complex, but because SharePoint is busy
Speaker 1: recalculating who's allowed to see which row you wanted granular security,
Speaker 1: you got molasses. Picture a librarian checking ID before handing
Speaker 1: out every individual page of a book. It's technically secure, yes,
Speaker 1: but you'll die of boredom before finishing chapter one. SharePoint
Speaker 1: does exactly that. Across your list views. The result performance
Speaker 1: collapses proportionally to how secure you tried to make it. True.
Speaker 1: Databased platforms handle this with row filtered views and role
Speaker 1: based access at query time, one efficient rule set applied dynamically,
Speaker 1: SharePoint brute forces it at load time. Genius in a
Speaker 1: sort of medieval way. Now add power apps to that equation.
Speaker 1: Every time the app opens a gallery, it authenticates through
Speaker 1: your context, fires off list queries, and evaluates those permissions
Speaker 1: one item at a time. Users think their device is slow,
Speaker 1: in reality, it's SharePoint playing bureaucrat, stamping each record approved
Speaker 1: for viewing before rendering the screen. Multiply that across hundreds
Speaker 1: of users, and the infrastructure wheezes like a fax machine.
Speaker 1: In twenty twenty four, this is where most teams start
Speaker 1: introducing shortcuts to save themselves. They duplicate data into unsecured
Speaker 1: lists for convenience's sake, or create automation that copies save subsets.
Speaker 1: Nightly congratulations you've just built shadow databases without integrity constraints,
Speaker 1: security becomes a patchwork of wishful thinking and with no
Speaker 1: centralized schema or role based system auditing, who can see
Speaker 1: what turns into an archaeological dig through broken inheritance chains.
Speaker 1: But security is only the first layer of dysfunction. Let's
Speaker 1: talk live cycle management, the grown up part of any
Speaker 1: software system. In proper database environments, you migrate through environments effortlessly, development, test, production, data,
Speaker 1: verse packages tables neatly inside power platform solutions. Esquel exports
Speaker 1: its schema in a single script SharePoint. It stares blankly,
Speaker 1: mutters something about list templates, and leaves you to figure
Speaker 1: out the rest. Moving a SharePoint data model between environments
Speaker 1: is like cloning Frankenstein. Theoretically possible, practically horrifying columns, loose types,
Speaker 1: choice values, mutate, look up IDs regenerate like chaotic DNA.
Speaker 1: Automated provisioning scripts attempt to recreate lists by name, only
Speaker 1: to discover that sharepoints internal identifiers don't align across sites.
Speaker 1: The resulting environment might look similar on the surface, but
Speaker 1: underneath it's a totally different creature stitch together with mismatched
Speaker 1: limbs and fragile wiring, and then you hit the content
Speaker 1: migration phase, where developers try to copy test data to production.
Speaker 1: SharePoint doesn't have true export import parity. Instead, you rely
Speaker 1: on Jason templates, PowerShell scripts, or third party tools that
Speaker 1: charge per gigabyte of despair. Migrate one thousand items, lose
Speaker 1: twenty lookups, and watch your power app crash because half
Speaker 1: its relationships now point to non existent records. That's not
Speaker 1: a migration, it's a funeral. Even versioning one of SharePoint's
Speaker 1: banner features becomes treacherous. The platform dutifully keeps historical copies
Speaker 1: of items, but power Apps doesn't integrate meaningfully with that
Speaker 1: version history. When something breaks, you can technically roll back,
Speaker 1: but you'll lose relational context in the process. Database tracks
Speaker 1: changes transactionally, you can restore state coherently. SharePoint just hands
Speaker 1: you a random past snapshot and says, good luck reconciling
Speaker 1: this mess. The tragedy here is cumulative. Each fragile list,
Speaker 1: each manual security rule, each handcrafted migration adds invisible weight.
Speaker 1: That's technical debt, the system equivalent of cholesterol. It clogs everything.
Speaker 1: Time that should go into improving your app instead goes
Speaker 1: into maintaining permission hierarchies and rebuilding lists that fail silently
Speaker 1: and the kicker. Most of that debt accruise because of
Speaker 1: a single flawed assumption that SharePoint was free, so cutting
Speaker 1: corners was justified. The next section rips the bandage of
Speaker 1: that illusion. Spoiler alert, the free option always charges interest. Later,
Speaker 1: the licensing trap and the free fallacy. Here's the root
Speaker 1: of this chaos. Accountants love free. The power platform license
Speaker 1: includes SharePoint, so using it feels thrifty. No approvals, no
Speaker 1: budget fights until later when the hidden technical debt arrives,
Speaker 1: disguised as maintenance, frustration and rebuild costs. Organizations don't pick
Speaker 1: SharePoint for capability. They pick it for optics where maximizing investment,
Speaker 1: they say, ignoring that those savings vanish once the app grows.
Speaker 1: Data verse costs more. Yes, but you're buying delegation, integrity,
Speaker 1: proper security, and ilam insurance that works when the fire starts.
Speaker 1: SharePoint tempts because it's easy, quick set up, instant demo applause.
Speaker 1: Then resources crawls, screens freeze, and it gets blamed. The
Speaker 1: saving ends up spent on consultants rebuilding it in data verse.
Speaker 1: This pattern repeats constantly free tools lwed teams into expensive
Speaker 1: consequences at scale. That false economy burns more hours, wages,
Speaker 1: and patients than any data verse license ever. Would you
Speaker 1: saved twenty dollars per user? Excellent? That'll cover a fraction
Speaker 1: of your next two hundred thousand dollars rebuilt. Microsoft didn't
Speaker 1: hide the truth. They built data Verse for scale because
Speaker 1: SharePoint never was. Ignoring that boundary isn't innovation, it's negligence.
Speaker 1: File cabinets don't run engines. Let's end this with the
Speaker 1: matter for everyone remembers. SharePoint is a filing cabinet. Beautifully labeled,
Speaker 1: permission controlled, and spacious databases are engines, precisely tuned, pressure tested,
Speaker 1: and built for sustained power. One stores the other, computes,
Speaker 1: confuse the two, and your power up becomes a car
Speaker 1: powered by stationary. Every symptom you've met, slow galleries, broken
Speaker 1: look ups, failed migrations stems from that category era. SharePoint
Speaker 1: isn't broken, your expectations are. It's not that Microsoft misled you.
Speaker 1: It's that you misapplied a product built for collaboration to
Speaker 1: a system demanding relational rigor. A filing cabinet can't negotiate
Speaker 1: transactions anymore than a stapler can run an a lit
Speaker 1: And if you genuinely need scale, concurrency, security, and integrity,
Speaker 1: stop living on borrowed code. Move the data to data
Speaker 1: Verse or seql where it belongs. Yes, licenses cost money,
Speaker 1: so does electricity, gravity, and every other law of physics
Speaker 1: your business depends on. So here's the blunt truth. Building
Speaker 1: an enterprise great power app on share Point is like
Speaker 1: balancing a skyscraper on Jello. It looks fine until someone moves.
Speaker 1: Then everything collapses slowly, expensively, and predictably. Don't wait for
Speaker 1: your app to become a cautionary screenshot. Migrate now, budget properly,
Speaker 1: and treat architecture as non negotiable. If this explanation saved
Speaker 1: you a future rebuild, repay the favor, subscribe, tap follow,
Speaker 1: enable notifications, and get each new episode delivered like dependable patches,
Speaker 1: on time every time. Keep watching, keep optimizing, and stop
Speaker 1: mistaking filing cabinets for engines