Query Streams VS ViewForge

Query Streams's answer

Query Streams makes it possible to stream live database data directly into Google Sheets and Microsoft Excel securely, without exposing SQL code, credentials, or modifying network firewalls. Unlike typical sync tools, it delivers true real-time streaming, enabling teams to share query outputs safely without granting database access. It combines the simplicity of spreadsheets with the power of live data, bridging the gap between IT and business users.

ViewForge's answer:

Three things. (1) Data ownership: ViewForge writes fitment as Shopify metaobjects native to your store — most competitors store fitment in their own database. (2) 8 verticals out of the box: auto, motorcycle, tractor, marine, power equipment, bicycle, printer, electronics — most competitors are automotive-only. (3) Smart Parse: extract fitment automatically from your existing product titles and descriptions instead of re-typing everything.

Query Streams's answer

Unlike competitors that rely on scheduled syncs or require complex configuration, Query Streams provides real-time data streaming, granular security, and zero network changes. Users can collaborate on live data without giving out SQL code or credentials, making it faster to set up, safer to share, and easier to scale. It supports a wide range of databases, offers parameterized spreadsheets, and keeps data refreshes truly live, not delayed by sync intervals.

ViewForge's answer:

Data ownership. Fitment lives in your Shopify metaobjects, so uninstalling does not take your compatibility data with it. Convermax, EasySearch and PartFinder all keep it in their own databases, and getting it back depends on their export tooling on the day you cancel.

Cost at the low end. The search widget, the compatibility table on the product page and the saved-vehicle garage are all on the free tier, up to 50 products, with no expiry. EasySearch puts the table and the garage behind its $75/month Premium plan. Convermax starts at $250/month.

Automotive and non-automotive coverage. Eight built-in templates, and fully custom templates from $19/month, for catalogs that do not decompose into Year/Make/Model at all.

Query Streams's answer

Our primary audience includes data analysts, finance teams, business operations professionals, and IT teams who need reliable, real-time access to data inside spreadsheets. Query Streams is designed for organizations that rely on Google Sheets or Excel for analysis and reporting but want to eliminate manual exports, delays, and security risks.

ViewForge's answer:

Shopify merchants whose customers need to know whether a part fits before they will buy it — and who do not have an engineer on staff to build that themselves.

Concretely: auto and truck parts retailers, powersports and motorcycle dealers, tractor and agricultural parts sellers, marine and outboard suppliers, small-engine and power equipment stores, bicycle and e-bike component shops, printer supply merchants, and electronics accessory sellers.

Catalog sizes run from a few dozen products on the free tier up into the tens of thousands; it is running in production on a catalog of roughly 40,000 SKUs. The common thread is not the industry — it is that "does this fit my thing" is the question deciding the sale.

Query Streams's answer

Query Streams was created to solve a common frustration: teams needed real-time data in spreadsheets, but existing solutions required complex integrations, risky credential sharing, or delayed syncs. We built Query Streams to make live database-to-spreadsheet connectivity secure, simple, and fast, so that analysts and decision-makers can work with up-to-date data without relying on engineering resources or manual processes.

ViewForge's answer:

ViewForge came out of agency work. Normal View was building for a parts retailer running roughly 12,000 SKUs who needed fitment search, and every app we evaluated stored the merchant's compatibility data in the vendor's own database.

That is a strange trade when you look at it directly. Fitment data is genuinely expensive to produce — it is weeks of work — and the merchant would not own the result. It would belong to whichever app happened to be installed that year.

Shopify metaobjects made a different answer possible: write fitment as native structured data inside the merchant's own store. The theme reads it, the Storefront API queries it, Admin GraphQL exports it, and it is still there after an uninstall. That decision is what the rest of the app is built around.

Everything else came from real catalogs rather than a roadmap. Eight verticals exist because a tractor catalog is not Year/Make/Model. Smart Parse exists because that retailer had already written fitment into 12,000 product titles, and nobody was ever going to retype them.

Query Streams's answer

Query Streams is built using modern, secure, and scalable web technologies designed for real-time data processing and seamless spreadsheet integration. The platform combines a reliable backend, secure communication protocols, and native integrations to deliver fast and dependable performance for teams of all sizes.

ViewForge's answer:

• TypeScript
• Shopify metaobjects, as the fitment data store
• Shopify theme app extensions for the storefront components: fitment search, saved-vehicle garage, compatibility table, product-page fit notice
• Shopify Storefront API, for querying fitment from the theme
• Shopify Admin GraphQL API, for writing and exporting fitment records
• NHTSA vehicle database, for VIN decoding
• ACES and PIES XML parsing, for automotive catalog import

Query Streams's answer

Finance teams and data analysts in mid-sized enterprises

SaaS companies integrating live reporting into spreadsheets

Business operations teams that require secure, real-time data sharing

IT departments enabling data access without exposing infrastructure