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Article3 min read

Timeweb Cloud Expands PostgreSQL: Solving Catalog Tasks Without a Separate Service

Managed PostgreSQL now includes additional extensions. We examine string similarity search, hierarchical data handling, and data warming using real-world e-commerce scenarios.

Nested product details arranged in a workshop layout
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For new store features, a separate service is often proposed immediately. Sometimes it is indeed necessary. However, the existing database can handle part of the workload if suitable extensions are available and the team understands their limitations.

On September 14, 2026, Timeweb Cloud added eight extensions for managed PostgreSQL. These include tools for working with hierarchies, similar strings, and preloading data into memory. These capabilities are valuable for custom catalog services and integrations using PostgreSQL.

Categories form a tree, not just a list

A store has sections, subsections, and nested groups. A query to "show everything in this branch" differs from selecting a single category. An extension for hierarchical data can make such queries more intuitive.

First, you must define the structural rules. Can a product belong to multiple branches? What happens when a section is moved? How are related collections updated? The new storage mechanism does not make these business decisions for you.

If a CMS uses a different schema and a different database system, installing an extension in a separate database will not change anything within it. For a store built on 1C-Bitrix, any changes to the storage require verification of supported configurations and integrations.

A similar string does not always mean the right product.

Fuzzy matching is useful when a query contains typos. However, similar article numbers may refer to incompatible parts, and short names can denote completely different items. Therefore, this feature cannot be judged solely by the reduction in empty results.

Prepare a set of real queries with correct answers. Specifically verify exact article numbers, common names, and typing errors. For some queries, suggestions are acceptable; for others, it is more important not to replace an exact match with an approximate one.

A good interface explains what similar options are shown and allows users to return to the original query. This reduces the likelihood of an incorrect selection.

Warming up helps only the necessary data.

Preloading tables or indexes can be beneficial after a restart. However, memory is not infinite: loading everything at once can evict data that is actually needed for the store's operations.

Measure the initial requests after startup and the normal mode. Then check which data causes latency and whether it can be reduced by targeted warming. The solution must be based on a specific scenario.

Additional database capabilities broaden developer choices. They are valuable when they enable simpler and more reliable solutions to proven tasks. The sheer number of connected extensions does not determine the quality of an online store.

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