{"id":24710,"date":"2025-02-20T05:32:19","date_gmt":"2025-02-20T13:32:19","guid":{"rendered":"https:\/\/www.pingcap.com\/?post_type=case-study&#038;p=24710"},"modified":"2025-04-29T19:26:31","modified_gmt":"2025-04-30T02:26:31","slug":"anteraja-scalable-high-performance-courier-management","status":"publish","type":"case-study","link":"https:\/\/www.pingcap.com\/ko\/case-study\/anteraja-scalable-high-performance-courier-management\/","title":{"rendered":"How Anteraja Ensures 50% Faster Response Times with Distributed SQL"},"content":{"rendered":"<p>As one of Indonesia\u2019s leading logistics companies, <a href=\"https:\/\/anteraja.id\/id\/\">Anteraja<\/a> has established itself as a trusted provider of courier and delivery services. With a robust network spanning the entire country, Anteraja caters to individual and corporate customers, offering reliable service and a commitment to customer satisfaction.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Challenge_Navigating_System_Overloads_and_Real-Time_Demands\"><\/span>The Challenge: Navigating System Overloads and Real-Time Demands<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Anteraja\u2019s rapid growth in Indonesia\u2019s logistics market presented unique operational challenges, particularly in its courier management system. The system, designed on a legacy database architecture, could not cope with the demands of an expanding customer base and surging transaction volumes. Although designed for batch processing, it struggled to cope with real-time demands. This resulted in high CPU usage, slow response times, and data inconsistencies.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"495\" src=\"https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-1024x495.jpg\" alt=\"\" class=\"wp-image-24756\" srcset=\"https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-1024x495.jpg 1024w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-300x145.jpg 300w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-768x371.jpg 768w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-1536x742.jpg 1536w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-2048x990.jpg 2048w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020105\/img_v3_02i3_c1a71578-259a-4cd4-85a9-ea6f0270273g-1440x696.jpg 1440w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\"><em>Figure 1: Anteraja&#8217;s Original Architecture <\/em><\/p>\n\n\n\n<p>The complexity of Anteraja\u2019s legacy database architecture significantly hindered the team&#8217;s ability to address the increasing demands.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>High CPU Usage<\/strong>: As order volumes surged, database CPU utilization climbed to 100% during peak times, causing severe slowdowns and long queues for critical transactions.<\/li>\n\n\n\n<li><strong>Slow Queries<\/strong>: Increased CPU load resulted in <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/identify-slow-queries\/\">degraded query performance<\/a>, delaying real-time updates on delivery statuses and prolonging transaction processing, frustrating both customers and internal teams.<\/li>\n\n\n\n<li><strong>Locking Issues<\/strong>: <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/high-concurrency-best-practices\">Concurrent transactions<\/a> overwhelmed the database\u2019s capacity, leading to frequent locking problems. Multiple processes attempting to access the same data caused bottlenecks, further slowing operations.<\/li>\n\n\n\n<li><strong>Database Freeze<\/strong>: During peak loads, the entire database would sometimes freeze, halting new data insertion and causing unprocessed transactions to accumulate. The only temporary fix\u2014restarting the database\u2014was disruptive and risky, especially during crucial periods.<\/li>\n\n\n\n<li><strong>Data Corruption Risk<\/strong>: Repeated restarts heightened the risk of data corruption, resulting in inaccurate order records and mismanaged deliveries, which undermined customer trust.<\/li>\n\n\n\n<li><strong>Package Delivery Delays<\/strong>: System downtime directly impacted operations, delaying package processing and delivery, eroding customer confidence, and increasing pressure on logistics teams to meet SLAs.<\/li>\n\n\n\n<li><strong>Temporary <\/strong><a href=\"https:\/\/www.pingcap.com\/ko\/blog\/database-sharding-defined\/\"><strong>Manual Sharding<\/strong><\/a><strong> Complexity<\/strong>: To manage the growing data load, the database was split into 40 partitions, distributing the load but significantly complicating system maintenance and query coordination, making troubleshooting resource-intensive.<\/li>\n<\/ul>\n\n\n\n<p>These challenges hindered Anteraja\u2019s ability to scale effectively and threatened its reputation for reliable service. The courier management system\u2019s limitations necessitated a more robust, scalable solution capable of handling the real-time demands of a modern logistics business.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Solution_Unifying_and_Streamlining_Operations_with_Distributed_SQL\"><\/span>The Solution: Unifying and Streamlining Operations with Distributed SQL<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>To address these challenges, Anteraja migrated its courier management system to <a href=\"https:\/\/www.pingcap.com\/ko\/\">\ud2f0DB<\/a>, a distributed SQL database renowned for its scalability and performance. This migration consolidated the 40 fragmented databases into a single TiDB cluster. TiDB\u2019s distributed architecture and horizontal scalability provided an efficient, resilient solution to meet Anteraja\u2019s growing needs.<\/p>\n\n\n\n<p>The new architecture streamlined operations, reducing complexity and ensuring smooth, real-time processing. TiDB\u2019s ability to scale horizontally and handle online transactional processing (OLTP) and online analytical processing (OLAP) workloads enabled Anteraja to maintain <a href=\"https:\/\/www.pingcap.com\/ko\/article\/mastering-tidb-performance-tuning-a-comprehensive-guide\/\">high performance under peak loads<\/a>.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"476\" src=\"https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-1024x476.jpg\" alt=\"\" class=\"wp-image-24757\" srcset=\"https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-1024x476.jpg 1024w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-300x139.jpg 300w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-768x357.jpg 768w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-1536x714.jpg 1536w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-2048x952.jpg 2048w, https:\/\/static.pingcap.com\/files\/2024\/12\/31020210\/img_v3_02i3_ee0b9c8f-be57-4b4f-b523-175876be160g-1440x669.jpg 1440w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\"><em>Figure 2: Anteraja&#8217;s New Architecture with TiDB <\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Result_Driving_Cost_Savings_Performance_and_Growth_with_TiDB\"><\/span>The Result: Driving Cost Savings, Performance, and Growth with TiDB<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The transition to TiDB proved to be a game-changer for Anteraja. The new database architecture provided the scalability and performance needed to handle peak workloads in the company\u2019s Courier Management System without disruptions. Key benefits included:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Improved Scalability: <\/strong>TiDB&#8217;s distributed architecture allowed Anteraja to handle increasing data volumes and transaction rates effortlessly.<\/li>\n\n\n\n<li><strong>Enhanced Performance:<\/strong> The database&#8217;s high-performance capabilities ensured faster response times by up to 50%, even during peak periods.<\/li>\n\n\n\n<li><strong>Reduced Costs: <\/strong>The migration to TiDB resulted in significant cost savings of up to 70% due to its efficient resource utilization.<\/li>\n\n\n\n<li><strong>Increased Reliability: <\/strong>The system&#8217;s stability and <a href=\"https:\/\/www.pingcap.com\/ko\/article\/ensuring-high-availability-with-tidb-in-modern-applications\/\">resilience to failures<\/a> have significantly improved customer satisfaction..\u00a0<\/li>\n<\/ul>\n\n\n\n<p>By embracing a <a href=\"https:\/\/www.pingcap.com\/ko\/article\/tidb-scalable-distributed-sql-for-real-time-analytics\/\">distributed SQL architecture<\/a>, Anteraja achieved significant gains in scalability, operational efficiency, cost savings, and system reliability. These improvements have enabled the company to easily handle growing data volumes, deliver exceptional customer experiences, and maintain its position as a leader in Indonesia\u2019s logistics industry.<\/p>","protected":false},"excerpt":{"rendered":"<p>As one of Indonesia\u2019s leading logistics companies, Anteraja has established itself as a trusted provider of courier and delivery services. With a robust network spanning the entire country, Anteraja caters to individual and corporate customers, offering reliable service and a commitment to customer satisfaction. The Challenge: Navigating System Overloads and Real-Time Demands Anteraja\u2019s rapid growth [&hellip;]<\/p>\n","protected":false},"author":282,"featured_media":25019,"template":"","tags":[349,16,9,111],"customer":[352],"industry":[113],"class_list":["post-24710","case-study","type-case-study","status-publish","has-post-thumbnail","hentry","tag-distributed-sql-database","tag-distributed-system","tag-scalability","tag-tidb","customer-anteraja","industry-logistics"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>How Anteraja Ensures 50% Faster Response Times with Distributed SQL<\/title>\n<meta name=\"description\" content=\"Learn how Anteraja optimized courier management with TiDB, achieving 50% faster performance, 70% cost savings, and greater reliability.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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