Fuego

Query

Visual Firestore query builder

Build Firestore queries visually with filters, vector search, JSON editing, query sharing and embeddings generated from text. No coding required.

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Capabilities

Query builder features

Visual interface

Build queries from forms and menus: where conditions with OR, starts-with and between, order by, limit, cursors, field selection and collection groups. On Enterprise databases, the pipeline builder chains stages you move up or down.

JSON editor

Edit queries as JSON with syntax highlighting, schema validation and autocompletion. Copy a query and paste it into another project to reuse it.

Query sharing

Copy a fuego:// link that opens the query in Fuego, export it as a .fuego file, copy it as JSON or generate SDK code for your documentation.

Save & organize

Save queries, bookmark your favorites and turn a saved query with a {{query}} placeholder into a global search filter. Scope each one to a collection, a collection group or a set of databases.

Query analysis

Explain shows the indexes a query uses and, with Analyze, its execution time, documents scanned and billable reads. The Index Advisor tells you which composite index a query needs.

Live count & validation

A live count shows how many documents match while you build, and invalid filters or incomplete stages are flagged before you run. With real-time on, classic query results keep updating.

Query types

Supported query types

Simple filters

Basic equality, comparison, and range queries on document fields with operators like ==, !=, <, <=, >, >=.

StartsWith queries

Quick shortcut for prefix matching queries. Search for documents where a field starts with a specific string value.

Between queries

Convenient shortcut for range queries: one between condition stands for a >= and a <= on the same field.

Vector search (findNearest)

Nearest-neighbor search on a vector field with cosine, Euclidean or dot product distance. Paste a query vector or generate one from text with OpenAI, Gemini, Cohere, Ollama or another provider you configure.

Array queries

array-contains and array-contains-any match values inside array fields; in and not-in match a field against a list of values.

Compound queries

Multiple conditions with AND/OR logic for complex filtering requirements across different fields.

Sorting & limits

Order results by multiple fields with ascending/descending options, pagination, and result limits.

Aggregation

On Firestore Enterprise, the pipeline aggregate stage groups documents and computes count, sum, average, minimum, maximum and more. Classic queries show a live document count.

Subcollections

Collection group queries search every collection with the same ID, at any depth, including subcollections.

Manage & share

Advanced query management

JSON editor & copy/paste

Work with queries as JSON:

  • Switch between visual and JSON editing modes
  • Copy query JSON to clipboard with one click
  • Paste a query copied from another project or shared as JSON
  • Syntax highlighting, schema validation and autocompletion for JSON
  • Export a query as a .fuego file and import it (old .json queries too)

Query sharing & collaboration

Share and reuse queries:

  • Copy a fuego:// link that opens the query in Fuego
  • Generate code for the Admin and Client SDKs
  • Make a saved query available in several projects and databases
  • Sync saved queries between machines with project sync
  • Hand teammates your saved queries with Share configuration

Organize

Save, organize & analyze queries

Save & favorites

Organize your queries for quick access:

  • Save frequently used queries
  • Bookmark favorite queries for the sidebar and Home page
  • Scope a query to a collection or collection group
  • Show only the queries valid for the open collection
  • Hide global search queries from the list
  • Jump to a saved query from the command palette

Global search integration

Turn saved queries into search filters:

  • Apply saved queries to global search
  • Run every saved global query in one search
  • Run a saved query on every top-level collection
  • Open a result's query in the explorer
  • Limit the search to selected projects
  • Open a result in a new window or in Quick View

Query analysis

See how a query runs and check your indexes:

  • Execution time (Explain → Analyze)
  • Index usage analysis
  • Missing index recommendations
  • Billable documents and index entries
  • Documents and index entries scanned
  • Find duplicate and overlapping indexes in the database

AI & search

Vector search & AI embeddings

Semantic search with findNearest

Run a nearest-neighbor search on a vector field with a query vector you paste or generate from text with the embedding provider you configure. Results come back closest first, so documents similar in meaning show up even without an exact match.

OpenAI embeddings

text-embedding-3-small and text-embedding-3-large with a configurable output dimension, plus the legacy text-embedding-ada-002. Default dimensions stay within the 2,048 Firestore allows.

Google Gemini

Gemini embedding models such as gemini-embedding-2 and gemini-embedding-001, through the Gemini API with an API key or through Vertex AI with a Google Cloud project and location. Text input, with a configurable dimension.

Cohere embeddings

Cohere embed-v4.0 with a configurable dimension, and the embed v3 English and multilingual models, including their light versions.

Custom models

Type any model name a provider offers, run local models through Ollama, or point an OpenAI-compatible provider at your own endpoint.

Vector search features

  • Generate a query vector from text, or paste one, without leaving the query builder
  • Pick the distance metric: cosine, Euclidean or dot product
  • Set an optional distance threshold and a result limit of up to 1,000 documents
  • Combine vector search with where filters in the same query
  • Return each result's distance in a field you name

Use cases

  • Semantic search across documents
  • Testing content recommendations based on similarity
  • Finding near-duplicate documents
  • Checking retrieval for RAG and question-answering apps
  • Finding similar products in a catalog

FAQ

Frequently asked questions

Can I build complex queries without coding?

Yes. Fuego's query builder lets you add where conditions with AND/OR, starts-with and between, order by, limit, cursors, field selection and collection group queries without writing code. You can also edit a query as JSON, validated against a schema as you type, and on Firestore Enterprise databases build pipeline queries stage by stage, including aggregations.

Does the query builder support vector search?

Yes. Turn on Vector search (find nearest) in the query builder, pick a vector field and a distance metric (cosine, Euclidean or dot product), then paste a query vector or generate one from text with an embedding provider you set up in Settings, such as OpenAI, Gemini, Vertex AI, Cohere or a local Ollama model. You can also set a distance threshold and a field that returns each result's distance.

Can I share and export queries?

Yes. You can edit a query as JSON, copy it to the clipboard, copy a fuego:// link to it, export it as a .fuego file, save and bookmark it, and generate code for the Admin SDK (Node.js, Python, Go, Java, C#, PHP, Ruby) or the Client SDK (TypeScript/JavaScript, Kotlin/Java, Swift).

Get started

Start building Firestore queries

Build Firestore queries visually, run vector searches, check them with Explain and the Index Advisor, then save and share them.

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