{"id":6104,"date":"2025-07-11T07:13:28","date_gmt":"2025-07-11T07:13:28","guid":{"rendered":"https:\/\/bentego.com\/real-time-gercek-zamanli-mi-batch-yigin-mi\/"},"modified":"2025-07-30T09:25:12","modified_gmt":"2025-07-30T09:25:12","slug":"real-time-gercek-zamanli-mi-batch-yigin-mi","status":"publish","type":"post","link":"https:\/\/bentego.com\/tr\/real-time-gercek-zamanli-mi-batch-yigin-mi\/","title":{"rendered":"Real-Time (Ger\u00e7ek Zamanl\u0131) m\u0131, Batch (Y\u0131\u011f\u0131n) m\u0131?"},"content":{"rendered":"

Veri i\u015fleme, i\u015f d\u00fcnyas\u0131nda do\u011fru kararlar\u0131 alman\u0131n en \u00f6nemli yap\u0131 ta\u015flar\u0131ndan biri. Ancak verileri ne zaman<\/strong> ve nas\u0131l <\/strong>i\u015fledi\u011finiz, operasyonel verimlilikten maliyetlere, hatta rekabet avantaj\u0131na kadar bir\u00e7ok noktada ciddi fark yaratabiliyor. Bu noktada kar\u015f\u0131m\u0131za iki temel yakla\u015f\u0131m \u00e7\u0131k\u0131yor: Real-Time<\/strong>(ger\u00e7ek zamanl\u0131)<\/strong> ve Batch (y\u0131\u011f\u0131n) <\/strong>i\u015fleme. Peki bu iki y\u00f6ntem aras\u0131ndaki fark tam olarak ne? Hangisi hangi durumda daha mant\u0131kl\u0131 olur? <\/p>\n

Toplu \u0130\u015fleme Nedir?<\/strong><\/h4>\n

Kesikli i\u015fleme; verilerin bir s\u00fcre toplan\u0131p, belirli aral\u0131klarla topluca i\u015flenmesi anlam\u0131na geliyor. Bu y\u00f6ntem genellikle arka planda, gecikme tolerans\u0131 olan i\u015flemler i\u00e7in kullan\u0131l\u0131yor. A\u015fa\u011f\u0131daki gibi kullan\u0131m alanlar\u0131 olduk\u00e7a yayg\u0131nd\u0131r: <\/p>\n

    \n
  • Ayl\u0131k faturaland\u0131rma sistemleri<\/li>\n
  • Raporlama ve analiz s\u00fcre\u00e7leri<\/li>\n
  • Veri ambar\u0131 (data warehouse) g\u00fcncellemeleri<\/li>\n
  • Log ve sistem kay\u0131tlar\u0131n\u0131n analizi<\/li>\n<\/ul>\n

    \u2705 Avantajlar\u0131:<\/strong><\/p>\n

      \n
    • B\u00fcy\u00fck veri setlerini verimli bir \u015fekilde i\u015fler<\/li>\n
    • Kaynak kullan\u0131m\u0131 planlamas\u0131 daha kolayd\u0131r<\/li>\n
    • \u0130\u015flem maliyeti genellikle daha d\u00fc\u015f\u00fckt\u00fcr<\/li>\n
    • S\u00fcre\u00e7ler kolayca otomatize edilebilir<\/li>\n<\/ul>\n

      Ancak, kararlar\u0131n h\u0131zl\u0131 al\u0131nmas\u0131 gereken senaryolarda bu y\u00f6ntem bazen yetersiz kalabilir. Verinin olu\u015ftu\u011fu ve aksiyona ge\u00e7me s\u00fcresi, karar kalitesini do\u011frudan etkileyebilir. <\/p>\n

      Ger\u00e7ek Zamanl\u0131 \u0130\u015fleme Nedir?<\/strong><\/h4>\n

      Ger\u00e7ek zamanl\u0131 i\u015fleme, veri olu\u015ftu\u011fu anda ya da birka\u00e7 saniye i\u00e7inde analiz edilip anlaml\u0131 \u00e7\u0131kt\u0131lara d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesini sa\u011flar. \u00d6zellikle anl\u0131k tepki gerektiren durumlarda olmazsa olmazd\u0131r. Kullan\u0131m alanlar\u0131ndan baz\u0131lar\u0131: <\/p>\n

        \n
      • Doland\u0131r\u0131c\u0131l\u0131k (sahtekarl\u0131k) tespiti<\/li>\n
      • Online teklif sistemleri<\/li>\n
      • IoT cihazlar\u0131ndan gelen verilerin anl\u0131k analizi<\/li>\n
      • Finansal i\u015flemlerde anl\u0131k risk kontrol\u00fc<\/li>\n
      • Trafik ya da u\u00e7u\u015f izleme sistemleri<\/li>\n<\/ul>\n

        \u2705 Avantajlar\u0131:<\/strong><\/p>\n

          \n
        • Anl\u0131k veriye h\u0131zl\u0131 \u015fekilde tepki verilebilir<\/li>\n
        • Canl\u0131 izleme ve g\u00f6rselle\u015ftirme sa\u011flanabilir<\/li>\n
        • Anormallikler h\u0131zl\u0131 tespit edilebilir<\/li>\n
        • Kullan\u0131c\u0131lara an\u0131nda bildirim veya \u00f6neri g\u00f6nderilebilir<\/li>\n<\/ul>\n

          Bu sistemler genellikle Kafka, Flink, Spark Streaming veya Evam gibi da\u011f\u0131t\u0131k veri i\u015fleme altyap\u0131lar\u0131yla \u00e7al\u0131\u015f\u0131r.<\/p>\n

          \"\"<\/p>\n

          \n
          \n
          <\/div>\n<\/div>\n<\/figure>\n

          Ger\u00e7ek Hayattan \u00d6rnekler<\/strong><\/h4>\n
            \n
          • Ger\u00e7ek Zamanl\u0131:<\/strong> Bir u\u00e7a\u011f\u0131n ini\u015f ve kalk\u0131\u015f bilgilerinin saniyeler i\u00e7inde kuleye ve yolculara aktar\u0131lmas\u0131.<\/li>\n
          • Parti:<\/strong> G\u00fcn sonunda t\u00fcm u\u00e7u\u015f verilerinin i\u015flenerek raporlanmas\u0131.<\/li>\n<\/ul>\n

            Peki Bentego Ne Yap\u0131yor?<\/strong><\/h4>\n

            Veri i\u015fleme mimarimizi, karar alma h\u0131z\u0131n\u0131 bir rekabet avantaj\u0131 olarak konumland\u0131ran kurumlara \u00f6zel olarak ger\u00e7ek zamanl\u0131 veri ak\u0131\u015f\u0131<\/strong> temelinde in\u015fa ediyoruz. Batch modellerin gecikme ve operasyonel atalet sorunlar\u0131n\u0131 a\u015fmak i\u00e7in t\u00fcm platform mimarimizi olay g\u00fcd\u00fcml\u00fc (olay bazl\u0131)<\/strong> yap\u0131lar ve ak\u0131\u015f i\u015fleme<\/strong> teknolojileri etraf\u0131nda \u015fekillendiriyoruz. <\/p>\n

            Geli\u015ftirdi\u011fimiz b\u00fcy\u00fck veri \u00e7\u00f6z\u00fcmlerinde Apache Kafka, Apache Flink, Apache Spark ve Kinesis benzeri ak\u0131\u015f motorlar\u0131 ve kompleks olay s\u00fcre\u00e7leri ile milisaniyelik gecikmeler veri i\u015fliyor; anl\u0131k analiz, uyar\u0131 sistemleri ve aksiyon tetikleyicileri ile entegre oluyoruz. Ayr\u0131ca, m\u00fc\u015fterilerin ihtiya\u00e7lar\u0131na g\u00f6re pazarlama ve otomasyon \u00fcr\u00fcnlerini konumland\u0131r\u0131yoruz. Pazarlama ve otomasyon konusunda EVAM ve PEGA gibi \u00fcr\u00fcnlerin partnerli\u011fini yap\u0131yoruz ve m\u00fc\u015fteri ihtiyac\u0131n\u0131 en iyi \u015fekilde kar\u015f\u0131layan \u00e7\u00f6z\u00fcm\u00fc sunuyoruz. <\/p>\n

            Yaln\u0131zca veri ak\u0131\u015f\u0131n\u0131 de\u011fil; veri ambar\u0131 eri\u015fimlerini, dashboard g\u00fcncellemelerini, uyar\u0131 mekanizmalar\u0131n\u0131 veya \u00e7e\u015fitli ileti\u015fim katmanlar\u0131 da ger\u00e7ek zamanl\u0131 kurguluyoruz. Bentego olarak teknik h\u0131z sa\u011flaman\u0131n yan\u0131nda, organizasyonel refleksin de g\u00fc\u00e7lenip, s\u00fcre\u00e7lerin daha iyi y\u00f6netilmesini sa\u011fl\u0131yoruz. <\/p>\n","protected":false},"excerpt":{"rendered":"

            Veri i\u015fleme, i\u015f d\u00fcnyas\u0131nda do\u011fru kararlar\u0131 alman\u0131n en \u00f6nemli yap\u0131 ta\u015flar\u0131ndan biri. Ancak verileri ne zaman ve nas\u0131l i\u015fledi\u011finiz, operasyonel verimlilikten maliyetlere, […]<\/p>\n","protected":false},"author":1,"featured_media":5925,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[87],"tags":[106,105,103,104,102],"class_list":["post-6104","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-apache-spark-tr","tag-gercek-zamanli-veri","tag-gercek-zamanli-veri-akisi","tag-toplu-isleme","tag-yeniligi"],"yoast_head":"\nReal-Time (Ger\u00e7ek Zamanl\u0131) m\u0131, Batch (Y\u0131\u011f\u0131n) m\u0131? - Bentego<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/bentego.com\/tr\/real-time-gercek-zamanli-mi-batch-yigin-mi\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Real-Time (Ger\u00e7ek Zamanl\u0131) m\u0131, Batch (Y\u0131\u011f\u0131n) m\u0131? - Bentego\" \/>\n<meta property=\"og:description\" content=\"Veri i\u015fleme, i\u015f d\u00fcnyas\u0131nda do\u011fru kararlar\u0131 alman\u0131n en \u00f6nemli yap\u0131 ta\u015flar\u0131ndan biri. 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