Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsCloud Firestore stores data in documents grouped into collections. Use a document read or a query to retrieve data, set() to create or replace it, update() to change selected fields, and delete() to remove it. Attach a snapshot listener when a screen needs ongoing updates. Client apps can also use cached data offline, subject to platform configuration and Firestore’s synchronization behavior.
How Firestore organizes data and reads it
A Firestore collection contains documents. A document has a path such as /cities/SF and can contain fields, nested objects, and subcollections. Queries can filter, sort, limit, and paginate results. The Firestore data model documentation describes how these pieces fit together.
Read one document or query a collection
Use a single-document read when you know the document path and need that record. Use a collection or query read when you need matching documents—for example, cities matching a condition, ordered by a field, with a result limit. These are distinct access patterns: in Security Rules, a direct document read is authorized with get, while a query/list operation is authorized with list.
Firestore Security Rules do not act as query filters. A query must be structured so the rules can prove that every document it could return is allowed; Firestore does not silently remove unauthorized results. See Security Rules conditions.
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How to create, replace, update, and delete documents
Document writes use different operations depending on whether you intend to replace a document or change only some fields. Use the client SDK for your platform or the appropriate server library; exact method names and setup differ by SDK.
set()writes a document at a known path. A normal set replaces the document’s contents; SDKs also provide merge options when you need to preserve existing fields.create(), where supported, is for creating a document only if it does not already exist.update()changes specified fields on an existing document. It fails if that document does not exist.delete()removes the document.
For related writes that must either all succeed or all fail, use a batched write. A batch can group set, update, and delete operations, but it cannot read data to decide what to write. If the decision depends on current data, use a transaction instead. Firestore requires transaction reads to happen before transaction writes. The transactions and batched writes guide explains both approaches.
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- The Google TV Streamer (4K) delivers your favorite entertainment quickly, easily, and personalized to you[1,2]
- HDMI 2.1 cable required (sold separately)
- See movies and TV shows from all your services right from your home screen[2]; and find new things to watch with tailored recommendations for everyone in your home based on their interests and viewing habits
- Watch live TV and access over 800 free channels from Pluto TV, Tubi, and more[3]; if you find an interesting show or movie on your TV, mobile app, or Google search, you can easily add it to your watchlist, so it’s ready when you are[2]
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How to keep a screen current with realtime listeners
Attach a snapshot listener to a document when one record must stay current, or to a query when a changing result set must stay current. Firestore sends an initial snapshot and then new snapshots as the listened-to document or query results change. Listener setup and callback syntax depend on the SDK; the realtime listeners guide includes platform-specific examples.
Keep listeners only as long as the screen or feature needs them, and remove or unsubscribe when that scope ends. This prevents callbacks from continuing after the UI no longer needs them. Reads associated with listeners can affect usage and cost as results are delivered or change; account for this when choosing a broad query or keeping a listener active for a long period.
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What happens when a client is offline
Firestore mobile and web clients can use local cached data while offline and synchronize local changes when connectivity returns. Firebase’s offline access documentation says persistence is enabled by default on Android and Apple platforms; on the web it is disabled by default and must be configured. Cached data is what the client can read while offline, so an offline read should not be treated as proof that the server currently has the same state.
When the device reconnects, local changes synchronize to the backend. If multiple changes conflict on the same document, Firestore uses last-write-wins behavior. Design application logic with that resolution in mind if users may edit the same document from multiple devices.
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Secure client and server access correctly
For mobile and web apps, pair Firebase Authentication with Firestore Security Rules. Rules can separately authorize get, list, create, update, and delete; rules match documents, so access to a subcollection needs an explicit matching rule. Never deploy an allow-all rule set. Start with the Security Rules getting-started guide.
Rules can also validate fields and prevent changes to fields that should remain immutable. The rules documentation describes using diff() to inspect changed fields: field-level rule controls. A rule update may take up to one minute to affect new queries and listeners, and up to 10 minutes to fully affect active listeners, according to Firebase’s rule deployment guidance.
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Privileged server client libraries have a different trust boundary: they use IAM and bypass Firestore Security Rules. Restrict server identities and credentials through IAM rather than relying on client rules to constrain those calls. See Firestore security overview.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose transactions, batches, and pagination for reliability
Use a transaction when a write depends on current data
Transactions are appropriate for read-modify-write logic that must be based on current stored values. Firestore may retry a transaction when concurrent changes cause contention. If it ultimately fails, the transaction is atomic: it does not leave a partial set of writes. Keep transaction work retry-safe, and perform all reads before issuing writes. Current service limits are documented in the transaction failure and limits guidance.
Use a batch when writes are related but need no reads
A batched write is atomic and suitable for a fixed group of create, update, or delete operations that should commit together. Since a batch does not read documents, it cannot safely choose its writes based on values fetched as part of that same operation.
Use cursors, not offsets, to paginate
For paginated query results, use a cursor based on document or field values rather than an offset. Firestore still incurs reads for documents skipped by an offset, so offsets can add cost without returning those documents. The query cursors guide shows cursor-based pagination.
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Test the workload you expect to run
Run load tests for high-rate workloads. Firestore’s single-document write capacity varies with contention and index fanout, so a general write-rate figure cannot guarantee that a particular workload will perform reliably. Where independent operations do not depend on one another, issue them asynchronously rather than unnecessarily waiting for each one in sequence. Firebase describes Firestore’s broader capabilities and integrations in its Firestore documentation.
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