How effectively you use information depends on the platform you choose. Different data types and business tasks require different solutions. According to TASS, the domestic DBMS market is growing by 25% per year, while 85% of new projects use relational or hybrid models. Relational DBMS store information in tables with a clear structure (rows and columns).
They use SQL to work with data, ensuring reliability and compliance with ACID rules (atomicity, consistency, isolation, durability). Such systems are widely used in banking, government agencies, and large corporations for core record systems where every entry must be accurate. For example, banks use relational databases to process transactions and maintain customer accounts. Their drawback is difficulty scaling under very high loads.
NoSQL systems Work with unstructured data: documents, graphs, or "key-value" pairs. They scale horizontally easily by adding servers to distribute the load. Large retailers and telecom operators use such solutions to analyze user behavior in real time. The downside is less strict data integrity control compared with relational DBMSs. Embedded DBMSs Work as part of the application without a separate server process.
They use few resources and do not require complex administration. Such solutions are used by mobile app developers, navigation software makers (for example, Yandex Navigator), and software for IoT devices. For example, navigation software uses an embedded database to cache maps. The main limitation is that they are not designed for multi-user work with large amounts of information. Master data management systems (MDM) create a single trusted source for key business objects: customers, products, employees.
They synchronize information across different company systems to avoid inconsistencies. MDM is indispensable in large corporations with extensive IT infrastructure (Evraz, T2, Rostelecom PJSC). It cleans data, removes duplication, and ensures consistency. Product information management software (PIM) centralizes product information: descriptions, specifications, images, prices. Manufacturers and retailers use PIM to quickly update catalogs across all sales channels.
This speeds up the launch of new products and improves data quality on websites and marketplaces Let's compare data management systems by use case and business value:
| System type | Best-fit scenarios | Business value |
|---|
| Relational DBMS | Financial operations, accounting systems | Ensures data accuracy and ACID compliance |
| NoSQL systems | Big Data, IoT, Content Platforms | Allows flexible scaling to match the load |
| Embedded databases | Mobile apps, IoT devices | Works without a separate server and saves resources |
| MDM systems | Large companies with fragmented data | Creates a single source of truth for customers or products |
| PIM systems | Retail, manufacturing, distribution | Centralizes management of product catalogs |
How to choose the right system The choice depends on the company's needs.
Below are the key criteria to evaluate before implementation. Data type and structure - clearly structured (tables) or heterogeneous (documents, graphs)? - Scalability requirements - do you need to add new servers quickly to handle growing load? - Transaction criticality - how important is 100% accuracy and consistency in every operation? - Budget and Resources - how much is the company ready to invest in deploying and supporting the system? - Team expertise - does the team have specialists to administer complex systems?
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