Business Context
The customer provides a digital business management system tailored for fast-moving consumer goods (FMCG) distributors. This system standardizes processes across procurement, warehousing, distribution, financial management, field operations, and customer management, helping distributors improve operational efficiency and decision-making through data-driven insights.
Core Functionalities
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Data-Driven Decision Support: Multi-dimensional data reports help identify risks related to sales, inventory, and financials, providing a scientific basis for decision-making.
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Comprehensive Business Process Management: Covers procurement, inventory, distribution, financials, market management, sales outreach, and reporting.
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Inventory Optimization: Real-time updates on stock levels and expiration dates reduce overstocking and shortages.
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Financial & Risk Control: Accounts receivable tracking, overdue reminders, and automated reconciliation lower financial risks.
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Product & Marketing Optimization: Sales reports by product and brand help refine product mix and marketing strategies.
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Seamless Online & Offline Operations: Integrates e-commerce store management with offline distribution.
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Intelligent Alerts: Automated notifications for stock shortages and expiring products improve operational efficiency.
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Delivery Efficiency Enhancement: Dynamic order-based route optimization improves order fulfillment capabilities.
The system aims to replace manual processes, reduce inefficiencies in inventory management, and enhance customer relationship management by leveraging real-time data and automation.
Original Architecture & Challenges
Legacy System Architecture
The customer's original system relied on a traditional data warehouse for structured data storage and Elasticsearch for full-text search. The architecture looked like this:
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1. Data Ingestion & Storage
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Transactional data (sales, inventory, orders) was batch-loaded into a cloud-based data warehouse for analytics.
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Product descriptions and unstructured data were indexed in Elasticsearch for full-text search.
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2. Query Execution & Reporting
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Business intelligence (BI) tools queried structured data for reports and dashboards.
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Elasticsearch queries handled product searches but could not filter by structured attributes like sales performance or stock levels.
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Pain Points in the Original System
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Delayed Data Updates: Data synchronization across systems was slow, causing reconciliation mismatches and outdated reports.
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Slow OLAP Queries: Large-scale aggregations (e.g., sales trends, inventory turnover)suffered from high latency.
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Multi-Modal Search Inefficiency: Searching across both Elasticsearch and structured data in the warehouse required separate queries and manual data stitching.
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Scalability Bottlenecks: Increased data volumes led to slow query performance and system instability.
New Architecture with Tacnode
With Tacnode, the customer unified structured data and full-text search, enabling real-time analytics and efficient multi-modal search. The new architecture:
1. Real-Time Data Processing
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Tacnode ingests structured, semi-structured (JSON), and unstructured (full-text) data in real time, replacing the previous batch-loaded data warehouse while integrating directly with Elasticsearch for full-text capabilities.
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Unlike the legacy setup, structured business data and full-text search are now accessible in a single system, enabling instant analytics and seamless query execution.
2. Omni-Search: Unified Multi-Modal Queries
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Tacnode's Omni-Search natively integrates full-text search with structured OLAP queries, allowing users to perform hybrid searches across structured attributes and text-based product descriptions in a single query.
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This eliminates the need to query Elasticsearch separately and manually join results, significantly improving search efficiency.
3. High-Performance OLAP & Query Execution
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Materialized views and real-time aggregations replace slow batch-processing queries from the previous data warehouse.
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Massively parallel processing (MPP) speeds up analytical queries, improving performance for dashboards and reports.
4. Scalability Without System Complexity
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While Tacnode does not replace the customer's existing transactional database, it completely replaces their data warehouse and Elasticsearch for analytics and search.
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Separation of compute and storage ensures linear scaling, allowing high concurrency and low-latency queries even as data volume and traffic grow.
Benefits of the New Architecture
Feature | Legacy System | Tacnode Solution |
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Data Updates | Batch processing, delayed updates | Real-time ingestion & updates |
Query Performance | High latency for analytics | 2x faster OLAP queries |
Multi-Modal Search | Separate queries in Elasticsearch & Data Warehouse | Omni-Search: Unified full-text & structured queries |
Scalability | Performance degradation under high loads | **Seamless horizontal scaling ** |
Tacnode's Solution & Impact
1. Real-Time Data Synchronization for Instant Business Insights
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Tacnode's high-concurrency, low-latency architecture ensured that business data was updated in real-time.
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Inventory updates were fully synchronized within seconds, eliminating discrepancies during stock reconciliation.
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Business dashboards instantly reflected the latest data, enabling proactive decision-making for inventory replenishment and sales strategy adjustments.
2. Fast OLAP Query Performance for Real-Time Analytics
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With Tacnode, query response times improved by 2x, significantly enhancing the user experience.
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Users could now generate interactive reports instantly, eliminating previous delays in filtering and visualization.
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Example: Dashboards that previously took several seconds to load now render results in real time, allowing teams to analyze business trends effortlessly.
3. Omni-Search: Unified Multi-Modal Search Across Structured and Full-Text Data
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Tacnode introduced Omni-Search, a solution that seamlessly integrates full-text search with structured OLAP queries, enabling users to perform hybrid searches across structured attributes and text-based product descriptions in a single query.
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This eliminated the need for manual data stitching between Elasticsearch and the data warehouse.
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Example: Users can now search for "orange juice" and instantly filter by sales performance and inventory status, retrieving results in milliseconds, a major improvement over the previous multi-step approach.
4. Horizontal Scalability & Long-Term System Stability
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Tacnode provided seamless horizontal scaling, allowing the system to handle increasing data volumes and user requests without performance degradation.
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The system automatically balanced workloads, ensuring smooth operation even as demand increased.
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Example: Despite a 15x increase in data volume and 4x higher traffic, Tacnode maintained stable and fast performance, ensuring uninterrupted service.
Business Outcomes
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Instant Business Insights: Real-time inventory updates eliminated reconciliation mismatches.
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Faster OLAP Query Performance: 2x improvement in query speeds resulted in a seamless, interactive user experience.
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Omni-Search Multi-Modal Query Efficiency: Integrated full-text and structured search into a single, fast query, eliminating manual stitching and inefficiencies.
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Scalability for Future Growth: The system now handles high traffic and large data volumes effortlessly, ensuring long-term stability.
Why Tacnode?
Tacnode's Postgres-compatible, distributed architecture provided a unified solution for real-time data ingestion, high-performance analytics, and multi-modal search. By introducing Omni-Search, it successfully solved the customer's data synchronization, query performance, search integration, and scalability challenges, making it the ideal choice for modern data-driven business platforms.