{"id":38353,"date":"2026-01-29T15:41:36","date_gmt":"2026-01-29T12:41:36","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/?p=38353"},"modified":"2026-01-29T15:41:36","modified_gmt":"2026-01-29T12:41:36","slug":"modern-uygulamalari-mongodb-ile-insa-etmek","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/modern-uygulamalari-mongodb-ile-insa-etmek\/","title":{"rendered":"Modern Uygulamalar\u0131 MongoDB ile \u0130n\u015fa Etmek"},"content":{"rendered":"<p><body><\/p>\n<h2>Modern Uygulamalar\u0131 MongoDB ile \u0130n\u015fa Etmek<\/h2>\n<p>G\u00fcn\u00fcm\u00fcz\u00fcn h\u0131zla de\u011fi\u015fen dijital d\u00fcnyas\u0131nda, modern uygulamalar esneklik, \u00f6l\u00e7eklenebilirlik ve y\u00fcksek performans gerektirir. Geleneksel ili\u015fkisel veritabanlar\u0131 belirli senaryolarda hala g\u00fc\u00e7l\u00fc olsa da, veri \u00e7e\u015fitlili\u011finin ve uygulama gereksinimlerinin artt\u0131\u011f\u0131 durumlarda NoSQL veritabanlar\u0131 \u00f6nemli avantajlar sunar. Bu rehberde, dok\u00fcman tabanl\u0131 NoSQL veritaban\u0131 olan MongoDB&#8217;nin modern uygulamalar geli\u015ftirirken neden bu kadar pop\u00fcler oldu\u011funu, temel \u00f6zelliklerini ve pratik kullan\u0131m\u0131n\u0131 ele alaca\u011f\u0131z.<\/p>\n<h2>MongoDB&#8217;nin Temelleri ve Neden Tercih Edilmeli?<\/h2>\n<p>MongoDB, a\u00e7\u0131k kaynakl\u0131, dok\u00fcman tabanl\u0131 bir veritaban\u0131d\u0131r. Verileri JSON benzeri BSON (Binary JSON) format\u0131nda depolar. Bu model, yap\u0131land\u0131r\u0131lm\u0131\u015f, yar\u0131 yap\u0131land\u0131r\u0131lm\u0131\u015f ve yap\u0131land\u0131r\u0131lmam\u0131\u015f verileri esnek bir \u015fekilde saklama olana\u011f\u0131 sunar. Peki, modern uygulamalar i\u00e7in MongoDB&#8217;yi \u00f6ne \u00e7\u0131karan temel \u00f6zellikler nelerdir?<\/p>\n<h3>Dok\u00fcman Modeli ve \u015eemas\u0131z Yap\u0131<\/h3>\n<ul>\n<li><strong>Esneklik:<\/strong> MongoDB&#8217;nin dok\u00fcman modeli, verileri do\u011fal bir \u015fekilde, uygulama kodunuzdaki nesnelerle uyumlu bir formatta depolaman\u0131za olanak tan\u0131r. Her dok\u00fcman farkl\u0131 alanlara sahip olabilir, bu da \u015fema de\u011fi\u015fikliklerinin kolayca y\u00f6netilmesini sa\u011flar.<\/li>\n<li><strong>Agile Geli\u015ftirme:<\/strong> Uygulama gereksinimleri de\u011fi\u015ftik\u00e7e veritaban\u0131 \u015femas\u0131n\u0131 de\u011fi\u015ftirmek zorunda kalmamak, geli\u015ftirme s\u00fcre\u00e7lerini h\u0131zland\u0131r\u0131r ve \u00e7evik metodolojilere m\u00fckemmel uyum sa\u011flar.<\/li>\n<li><strong>G\u00f6m\u00fcl\u00fc Dok\u00fcmanlar:<\/strong> \u0130li\u015fkisel veritabanlar\u0131nda &#8220;join&#8221; operasyonlar\u0131 gerektiren bir\u00e7ok senaryoyu, ilgili verileri tek bir dok\u00fcman i\u00e7inde g\u00f6merek \u00e7\u00f6zebilirsiniz. Bu, okuma performans\u0131n\u0131 art\u0131r\u0131r ve karma\u015f\u0131kl\u0131\u011f\u0131 azalt\u0131r.<\/li>\n<\/ul>\n<h3>Y\u00fcksek Performans ve \u00d6l\u00e7eklenebilirlik<\/h3>\n<ul>\n<li><strong>Y\u00fcksek Performans:<\/strong> MongoDB, verileri bellekte tutma yetene\u011fi (working set), indeksleme mekanizmalar\u0131 ve optimize edilmi\u015f sorgu motoru sayesinde y\u00fcksek okuma ve yazma performanslar\u0131 sunar.<\/li>\n<li><strong>Yatay \u00d6l\u00e7eklenebilirlik (Sharding):<\/strong> B\u00fcy\u00fck veri setleri ve y\u00fcksek trafikli uygulamalar i\u00e7in MongoDB, verileri birden fazla sunucuya (shard) da\u011f\u0131tarak yatay \u00f6l\u00e7eklenebilirli\u011fi destekler. Bu, sistemin kapasitesini kolayca art\u0131rman\u0131za olanak tan\u0131r.<\/li>\n<li><strong>Y\u00fcksek Eri\u015filebilirlik (Replica Sets):<\/strong> Replica Set&#8217;ler, verilerin birden fazla sunucuda kopyalanmas\u0131n\u0131 sa\u011flayarak veri kayb\u0131n\u0131 \u00f6nler ve birincil sunucunun \u00e7\u00f6kmesi durumunda otomatik failover ile kesintisiz hizmet sunar.<\/li>\n<\/ul>\n<h3>Zengin Sorgu Dili ve \u00d6zellikler<\/h3>\n<ul>\n<li><strong>G\u00fc\u00e7l\u00fc Sorgu Dili:<\/strong> MongoDB, filtreleme, s\u0131ralama, projeksiyon, toplama (aggregation) gibi zengin sorgu yetenekleri sunar. Agregasyon Framework&#8217;\u00fc, karma\u015f\u0131k veri analizi ve raporlama i\u00e7in olduk\u00e7a g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r.<\/li>\n<li><strong>Co\u011frafi Sorgular (Geospatial Queries):<\/strong> Konum tabanl\u0131 uygulamalar i\u00e7in \u00f6zel co\u011frafi indeksler ve sorgular destekler.<\/li>\n<li><strong>Tam Metin Arama (Full-Text Search):<\/strong> Metin tabanl\u0131 i\u00e7eriklerde h\u0131zl\u0131 ve etkili arama yapma yetene\u011fi sunar.<\/li>\n<\/ul>\n<h2>Modern Uygulama Mimarilerinde MongoDB&#8217;nin Yeri<\/h2>\n<p>MongoDB, esnek yap\u0131s\u0131 ve performans odakl\u0131 \u00f6zellikleriyle modern uygulama mimarileri i\u00e7in ideal bir se\u00e7imdir.<\/p>\n<h3>Mikroservisler ve Polyglot Persistence<\/h3>\n<p>Mikroservis mimarilerinde her hizmetin kendi veri deposuna sahip olmas\u0131 yayg\u0131n bir yakla\u015f\u0131md\u0131r (polyglot persistence). MongoDB, \u00f6zellikle belge tabanl\u0131 verilerle \u00e7al\u0131\u015fan veya h\u0131zl\u0131 iterasyon gerektiren mikroservisler i\u00e7in m\u00fckemmel bir uyum sa\u011flar. Her mikroservis, kendi veri modelini ve veritaban\u0131n\u0131 se\u00e7me \u00f6zg\u00fcrl\u00fc\u011f\u00fcne sahip oldu\u011fundan, MongoDB&#8217;nin esnekli\u011fi bu senaryoda parlar.<\/p>\n<h3>Sunucusuz (Serverless) Uygulamalar ve Ger\u00e7ek Zamanl\u0131 Veri \u0130\u015fleme<\/h3>\n<p>AWS Lambda, Azure Functions veya Google Cloud Functions gibi sunucusuz ortamlarda geli\u015ftirme yaparken, y\u00f6netilen bir veritaban\u0131 hizmeti kullanmak kritik \u00f6neme sahiptir. MongoDB Atlas, tam olarak y\u00f6netilen bir bulut veritaban\u0131 hizmeti sunarak sunucusuz uygulamalarla sorunsuz entegrasyon sa\u011flar. Ayr\u0131ca, MongoDB Change Streams \u00f6zelli\u011fi, veritaban\u0131ndaki de\u011fi\u015fiklikleri ger\u00e7ek zamanl\u0131 olarak yakalayarak event-driven (olay tabanl\u0131) mimariler ve ger\u00e7ek zamanl\u0131 analiz sistemleri i\u00e7in g\u00fc\u00e7l\u00fc bir temel olu\u015fturur.<\/p>\n<h3>B\u00fcy\u00fck Veri ve IoT Uygulamalar\u0131<\/h3>\n<p>IoT cihazlar\u0131ndan gelen s\u00fcrekli ve \u00e7e\u015fitli veri ak\u0131\u015f\u0131n\u0131 depolamak ve i\u015flemek, geleneksel veritabanlar\u0131 i\u00e7in zorlay\u0131c\u0131 olabilir. MongoDB&#8217;nin \u015femas\u0131z yap\u0131s\u0131 ve y\u00fcksek yazma performans\u0131, IoT sens\u00f6r verileri gibi b\u00fcy\u00fck ve s\u00fcrekli de\u011fi\u015fen veri setlerini etkin bir \u015fekilde y\u00f6netmek i\u00e7in idealdir. Agregasyon yetenekleri ise bu veriler \u00fczerinde h\u0131zl\u0131 analizler yap\u0131lmas\u0131na olanak tan\u0131r.<\/p>\n<h2>MongoDB ile Uygulama Geli\u015ftirme Pratikleri<\/h2>\n<p>\u015eimdi MongoDB ile temel CRUD (Create, Read, Update, Delete) operasyonlar\u0131n\u0131 ve indeksleme kullan\u0131m\u0131n\u0131 Node.js s\u00fcr\u00fcc\u00fcs\u00fc \u00fczerinden inceleyelim. Bu \u00f6rnekler, temel bir modern web uygulamas\u0131nda nas\u0131l kullan\u0131laca\u011f\u0131na dair pratik bir bak\u0131\u015f a\u00e7\u0131s\u0131 sunacakt\u0131r.<\/p>\n<h3>Ba\u011flant\u0131 Kurma<\/h3>\n<p>\u0130lk ad\u0131m, uygulaman\u0131z\u0131n MongoDB veritaban\u0131na ba\u011flanmas\u0131d\u0131r. Genellikle bir ba\u011flant\u0131 dizesi (connection string) kullan\u0131l\u0131r.<\/p>\n<pre><code class=\"language-javascript\">\nconst { MongoClient, ObjectId } = require('mongodb');\n\n\/\/ MongoDB ba\u011flant\u0131 dizesi (yerel veya Atlas URI)\nconst uri = \"mongodb:\/\/localhost:27017\"; \/\/ Yerel MongoDB i\u00e7in\n\/\/ const uri = \"mongodb+srv:\/\/<username>:<password>@<cluster-url>\/test?retryWrites=true&w=majority\"; \/\/ MongoDB Atlas i\u00e7in\n\nconst client = new MongoClient(uri);\n\nasync function connectDB() {\n    try {\n        await client.connect();\n        console.log(\"MongoDB'ye ba\u015far\u0131yla ba\u011fland\u0131!\");\n        return client.db(\"modernUygulamaDB\"); \/\/ Kullanmak istedi\u011finiz veritaban\u0131 ad\u0131\n    } catch (e) {\n        console.error(\"MongoDB ba\u011flant\u0131 hatas\u0131:\", e);\n        process.exit(1); \/\/ Ba\u011flant\u0131 hatas\u0131nda uygulamadan \u00e7\u0131k\n    }\n}\n    <\/code><\/pre>\n<h3>Veri Ekleme (Create)<\/h3>\n<p>Yeni bir dok\u00fcman\u0131 bir koleksiyona eklemek i\u00e7in <code>insertOne()<\/code> veya birden fazla dok\u00fcman\u0131 eklemek i\u00e7in <code>insertMany()<\/code> kullan\u0131r\u0131z.<\/p>\n<pre><code class=\"language-javascript\">\nasync function createPost(db) {\n    const posts = db.collection(\"posts\"); \/\/ 'posts' koleksiyonunu se\u00e7\n    const newPost = {\n        title: \"MongoDB ile Modern Uygulamalar\",\n        author: \"Alperen Y\u0131lmaz\",\n        content: \"Bu rehber, MongoDB'nin temel \u00f6zelliklerini ve kullan\u0131m\u0131n\u0131 anlat\u0131yor.\",\n        tags: [\"mongodb\", \"nodejs\", \"web-dev\"],\n        createdAt: new Date()\n    };\n    const result = await posts.insertOne(newPost);\n    console.log(<code>Yeni post eklendi: ${result.insertedId}<\/code>);\n    return result.insertedId;\n}\n    <\/code><\/pre>\n<h3>Veri Okuma (Read)<\/h3>\n<p>Dok\u00fcmanlar\u0131 sorgulamak i\u00e7in <code>find()<\/code> ve tek bir dok\u00fcman\u0131 almak i\u00e7in <code>findOne()<\/code> kullan\u0131l\u0131r. <code>find()<\/code> bir cursor d\u00f6nd\u00fcr\u00fcr ve \u00fczerinde d\u00f6ng\u00fc yap\u0131lmas\u0131 veya <code>toArray()<\/code> ile listeye d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesi gerekir.<\/p>\n<pre><code class=\"language-javascript\">\nasync function findPosts(db) {\n    const posts = db.collection(\"posts\");\n    \/\/ 'mongodb' etiketine sahip ve 'modernUygulamaDB' veritaban\u0131nda olu\u015fturulmu\u015f postlar\u0131 bul\n    const query = { tags: \"mongodb\", \"author\": \"Alperen Y\u0131lmaz\" };\n    const cursor = posts.find(query);\n\n    console.log(\"\\nBulunan Postlar:\");\n    await cursor.forEach(doc => console.log(doc));\n\n    \/\/ Tek bir post bulma\n    const singlePost = await posts.findOne({ title: \"MongoDB ile Modern Uygulamalar\" });\n    console.log(\"\\nTek bir post:\", singlePost);\n}\n    <\/code><\/pre>\n<h3>Veri G\u00fcncelleme (Update)<\/h3>\n<p>Mevcut dok\u00fcmanlar\u0131 g\u00fcncellemek i\u00e7in <code>updateOne()<\/code> veya <code>updateMany()<\/code> kullan\u0131l\u0131r. Genellikle <code>$set<\/code> operat\u00f6r\u00fc ile belirli alanlar g\u00fcncellenir.<\/p>\n<pre><code class=\"language-javascript\">\nasync function updatePost(db, postId) {\n    const posts = db.collection(\"posts\");\n    const result = await posts.updateOne(\n        { _id: new ObjectId(postId) }, \/\/ Belirli ID'ye sahip postu bul\n        { $set: { content: \"G\u00fcncellenmi\u015f i\u00e7erik: MongoDB, modern uygulamalar i\u00e7in harika bir se\u00e7imdir.\", lastModified: new Date() } } \/\/ Content alan\u0131n\u0131 g\u00fcncelle\n    );\n    console.log(<code>\\n${result.modifiedCount} post g\u00fcncellendi.<\/code>);\n}\n    <\/code><\/pre>\n<h3>Veri Silme (Delete)<\/h3>\n<p>Dok\u00fcmanlar\u0131 silmek i\u00e7in <code>deleteOne()<\/code> veya <code>deleteMany()<\/code> kullan\u0131l\u0131r.<\/p>\n<pre><code class=\"language-javascript\">\nasync function deletePost(db, postId) {\n    const posts = db.collection(\"posts\");\n    const result = await posts.deleteOne({ _id: new ObjectId(postId) });\n    console.log(<code>\\n${result.deletedCount} post silindi.<\/code>);\n}\n    <\/code><\/pre>\n<h3>\u0130ndeksleme<\/h3>\n<p>Performans\u0131 art\u0131rmak i\u00e7in indeksler kritik \u00f6neme sahiptir. S\u0131k\u00e7a sorgulanan alanlara indeks eklenmelidir.<\/p>\n<pre><code class=\"language-javascript\">\nasync function createIndexes(db) {\n    const posts = db.collection(\"posts\");\n    await posts.createIndex({ author: 1 }); \/\/ Yazar ad\u0131na g\u00f6re sorgular\u0131 h\u0131zland\u0131r\n    await posts.createIndex({ tags: 1 });   \/\/ Etiketlere g\u00f6re sorgular\u0131 h\u0131zland\u0131r\n    console.log(\"\\n\u0130ndeksler olu\u015fturuldu.\");\n}\n    <\/code><\/pre>\n<h3>Uygulama Ak\u0131\u015f\u0131<\/h3>\n<pre><code class=\"language-javascript\">\nasync function run() {\n    const db = await connectDB();\n    if (!db) return;\n\n    try {\n        await createIndexes(db);\n        const newPostId = await createPost(db);\n        await findPosts(db);\n        await updatePost(db, newPostId);\n        await findPosts(db); \/\/ G\u00fcncellenmi\u015f postu tekrar oku\n        \/\/ await deletePost(db, newPostId); \/\/ \u0130sterseniz silme i\u015flemini test edebilirsiniz\n    } finally {\n        await client.close();\n        console.log(\"MongoDB ba\u011flant\u0131s\u0131 kapat\u0131ld\u0131.\");\n    }\n}\n\nrun();\n    <\/code><\/pre>\n<h2>Performans ve \u00d6l\u00e7eklenebilirlik \u0130\u00e7in \u0130pu\u00e7lar\u0131<\/h2>\n<p>MongoDB ile y\u00fcksek performansl\u0131 ve \u00f6l\u00e7eklenebilir uygulamalar geli\u015ftirmek i\u00e7in baz\u0131 en iyi uygulamalar\u0131 g\u00f6z \u00f6n\u00fcnde bulundurmak \u00f6nemlidir:<\/p>\n<ul>\n<li><strong>Do\u011fru Veri Modellemesi:<\/strong>\n<ul>\n<li><strong>G\u00f6m\u00fcl\u00fc vs. Referansl\u0131 Dok\u00fcmanlar:<\/strong> \u0130li\u015fkisel olarak s\u0131k\u00e7a birlikte eri\u015filen verileri tek bir dok\u00fcman i\u00e7inde g\u00f6mmek (embedded documents) okuma performans\u0131n\u0131 art\u0131r\u0131r. \u00c7ok b\u00fcy\u00fck veya dinamik olarak b\u00fcy\u00fcyen ili\u015fkilerde ise referansl\u0131 dok\u00fcmanlar kullanmak daha mant\u0131kl\u0131 olabilir.<\/li>\n<li><strong>Dizi Kullan\u0131m\u0131:<\/strong> K\u00fc\u00e7\u00fck, s\u0131n\u0131rl\u0131 say\u0131da eleman\u0131 olan listeleri (\u00f6rn: etiketler, yorumlar) dizi olarak g\u00f6mmek performans\u0131 iyile\u015ftirir. Ancak dizilerin \u00e7ok b\u00fcy\u00fcmemesine dikkat edilmelidir.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Etkin \u0130ndeksleme:<\/strong>\n<ul>\n<li>Sorgular\u0131n\u0131zdaki filtre (<code>find()<\/code>, <code>$match<\/code>), s\u0131ralama (<code>sort()<\/code>) ve projeksiyon (<code>$project<\/code>) alanlar\u0131na uygun indeksler olu\u015fturun.<\/li>\n<li>Bile\u015fik indeksler (compound indexes) birden fazla alan\u0131 i\u00e7eren sorgular i\u00e7in kritiktir.<\/li>\n<li>Benzersiz indeksler (unique indexes) veri b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc sa\u011flar.<\/li>\n<li>TTL (Time-To-Live) indeksleri, belirli bir s\u00fcre sonra otomatik olarak silinmesi gereken veriler (\u00f6rn: oturum bilgileri, loglar) i\u00e7in kullan\u0131\u015fl\u0131d\u0131r.<\/li>\n<li>\u0130ndekslerin RAM&#8217;e s\u0131\u011fd\u0131\u011f\u0131ndan emin olun.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Sorgu Optimizasyonu:<\/strong>\n<ul>\n<li><code>explain()<\/code> metodunu kullanarak sorgular\u0131n\u0131z\u0131n performans\u0131n\u0131 analiz edin ve dar bo\u011fazlar\u0131 tespit edin.<\/li>\n<li>Gereksiz tam koleksiyon taramalar\u0131ndan ka\u00e7\u0131n\u0131n.<\/li>\n<li>B\u00fcy\u00fck sonu\u00e7 setleri d\u00f6nd\u00fcr\u00fcrken projeksiyonlar\u0131 (sadece ihtiyac\u0131n\u0131z olan alanlar\u0131 se\u00e7me) kullan\u0131n.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Replica Sets ve Sharding Kullan\u0131m\u0131:<\/strong>\n<ul>\n<li><strong>Replica Sets:<\/strong> \u00dcretim ortamlar\u0131nda her zaman en az 3 \u00fcyeli bir replica set kullan\u0131n. Bu, y\u00fcksek eri\u015filebilirlik ve veri kayb\u0131na kar\u015f\u0131 koruma sa\u011flar. Okuma y\u00fck\u00fcn\u00fc ikincil d\u00fc\u011f\u00fcmlere da\u011f\u0131tarak performans\u0131 art\u0131rabilirsiniz.<\/li>\n<li><strong>Sharding:<\/strong> Veri hacminiz terabaytlar\u0131 a\u015f\u0131yorsa veya \u00e7ok y\u00fcksek yazma\/okuma trafi\u011finiz varsa sharding&#8217;i d\u00fc\u015f\u00fcn\u00fcn. Do\u011fru shard anahtar\u0131 se\u00e7imi, sharding&#8217;in etkinli\u011fi i\u00e7in hayati \u00f6nem ta\u015f\u0131r.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Donan\u0131m ve Bulut Se\u00e7imi:<\/strong>\n<ul>\n<li>SSD diskler, y\u00fcksek I\/O performans\u0131n\u0131 garanti eder.<\/li>\n<li>Yeterli RAM, veritaban\u0131n\u0131n &#8220;working set&#8221;ini bellekte tutmas\u0131na yard\u0131mc\u0131 olur, bu da disk I\/O&#8217;sunu azalt\u0131r ve sorgular\u0131 h\u0131zland\u0131r\u0131r.<\/li>\n<li>MongoDB Atlas gibi y\u00f6netilen bir bulut hizmeti kullanmak, altyap\u0131 y\u00f6netimi y\u00fck\u00fcn\u00fc azalt\u0131r ve \u00f6l\u00e7eklenebilirlik, yedekleme gibi konularda kolayl\u0131k sa\u011flar.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h2>Sonu\u00e7 ve S\u0131k\u00e7a Sorulan Sorular (SSS)<\/h2>\n<p>MongoDB, modern uygulama geli\u015ftirmenin getirdi\u011fi zorluklara esnek, \u00f6l\u00e7eklenebilir ve performansl\u0131 bir \u00e7\u00f6z\u00fcm sunar. Dok\u00fcman tabanl\u0131 yap\u0131s\u0131, \u00e7evik geli\u015ftirme s\u00fcre\u00e7lerini desteklerken, g\u00fc\u00e7l\u00fc \u00f6zellikleri sayesinde mikroservislerden IoT uygulamalar\u0131na kadar geni\u015f bir yelpazede ba\u015far\u0131l\u0131 bir \u015fekilde kullan\u0131labilir. Do\u011fru veri modellemesi ve optimizasyon teknikleriyle birle\u015fti\u011finde, MongoDB uygulamalar\u0131n\u0131z\u0131n veri katman\u0131nda sa\u011flam bir temel olu\u015fturacakt\u0131r.<\/p>\n<h3>S\u0131k\u00e7a Sorulan Sorular (SSS)<\/h3>\n<dl>\n<dt>MongoDB ACID uyumlu mu?<\/dt>\n<dd>MongoDB, tek bir dok\u00fcman seviyesinde atomik (Atomicity), tutarl\u0131 (Consistency), izole (Isolation) ve dayan\u0131kl\u0131 (Durability) i\u015flemler i\u00e7in ACID uyumlulu\u011fu sa\u011flar. 4.0 s\u00fcr\u00fcm\u00fcnden itibaren \u00e7oklu dok\u00fcman i\u015flemleri i\u00e7in de ACID garantisi sunar.<\/dd>\n<dt>MongoDB&#8217;de &#8220;join&#8221; i\u015flemleri nas\u0131l yap\u0131l\u0131r?<\/dt>\n<dd>MongoDB&#8217;nin temel felsefesi verileri m\u00fcmk\u00fcn oldu\u011funca bir arada tutmakt\u0131r (g\u00f6m\u00fcl\u00fc dok\u00fcmanlar). Ancak ili\u015fkisel verilere ihtiya\u00e7 duyuldu\u011funda, <code>$lookup<\/code> operat\u00f6r\u00fc ile agregasyon framework&#8217;\u00fc i\u00e7inde join benzeri i\u015flemler yapabilir veya uygulama katman\u0131nda birden fazla sorgu yaparak verileri birle\u015ftirebilirsiniz.<\/dd>\n<dt>\u015eemas\u0131z olmak veri b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc nas\u0131l etkiler?<\/dt>\n<dd>MongoDB tamamen \u015femas\u0131z de\u011fildir, &#8220;\u015fema esnekli\u011fi&#8221; sunar. Bu, farkl\u0131 dok\u00fcmanlar\u0131n farkl\u0131 alanlara sahip olabilece\u011fi anlam\u0131na gelir. Veri b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc sa\u011flamak i\u00e7in uygulama katman\u0131nda do\u011frulama (validation) mekanizmalar\u0131 kullanabilir veya MongoDB&#8217;nin 5.0 s\u00fcr\u00fcm\u00fcnden itibaren gelen &#8220;Schema Validation&#8221; \u00f6zelli\u011fini kullanarak belirli koleksiyonlar i\u00e7in \u015fema kurallar\u0131 tan\u0131mlayabilirsiniz.<\/dd>\n<dt>MongoDB ne zaman kullan\u0131lmamal\u0131d\u0131r?<\/dt>\n<dd>E\u011fer uygulaman\u0131z\u0131n verileri y\u00fcksek derecede ili\u015fkisel ve karma\u015f\u0131k &#8220;join&#8221; i\u015flemlerine yo\u011fun bir \u015fekilde ihtiya\u00e7 duyuyorsa, veya kat\u0131 ACID garantileri (\u00e7oklu dok\u00fcmanlar aras\u0131 atomik i\u015flemler) birincil \u00f6nceli\u011finizse, ili\u015fkisel veritabanlar\u0131 daha uygun olabilir. Ancak \u00e7o\u011fu modern web uygulamas\u0131 senaryosunda MongoDB g\u00fc\u00e7l\u00fc bir alternatiftir.<\/dd>\n<\/dl>\n<p><\/body><\/p>\n","protected":false},"excerpt":{"rendered":"Modern Uygulamalar\u0131 MongoDB ile \u0130n\u015fa Etmek\n    G\u00fcn\u00fcm\u00fcz\u00fcn h\u0131zla de\u011fi\u015fen dijital d\u00fcnyas\u0131nda, modern uygulamalar esneklik, \u00f6l\u00e7eklenebi","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[676],"tags":[],"class_list":{"0":"post-38353","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-mongodb","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.5 (Yoast SEO v25.3.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Modern Uygulamalar\u0131 MongoDB ile \u0130n\u015fa Etmek - 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