Choose a data or storage product (9)·续

K2 is ideal for:

  • Moving large volumes of event data, with pricing based on data volume rather than the number of messages.
  • Delivering the same events to multiple independent consumers. For example, events from your applications can be read by an alerting system, a system that stores them durably, and a system that builds machine learning features.
  • Retaining events so that consumers can replay them, or so that a new consumer can read events produced before it was added.

Use Queues when each message is a unit of work that needs to be completed, retried, and tracked individually. Use K2 when you produce and consume records in bulk, and what matters is that every record is processed rather than the state of any one record.

To get started with K2:

Hyperdrive

Hyperdrive is a service that accelerates queries you make to MySQL and Postgres databases, making it faster to access your data from across the globe, irrespective of your users’ location.

Hyperdrive allows you to:

  • Connect to an existing database from Workers without connection overhead.
  • Cache frequent queries across Cloudflare's global network to reduce response times on highly trafficked content.
  • Reduce load on your origin database with connection pooling.

To get started with Hyperdrive:

Basin Pipelines

Basin Pipelines is a streaming ingestion service that allows you to ingest high volumes of real time data, without managing any infrastructure.

Basin Pipelines allows you to:

  • Ingest data at extremely high throughput (tens of thousands of records per second or more)
  • Batch and write data directly to object storage, ready for querying
  • (Future) Transform and aggregate data during ingestion

To get started with Basin Pipelines:

Analytics Engine

Analytics Engine is Cloudflare's time-series and metrics database that allows you to write unlimited-cardinality analytics at scale using a built-in API to write data points from Workers and query that data using SQL directly.

Analytics Engine allows you to:

  • Expose custom analytics to your own customers
  • Build usage-based billing systems
  • Understand the health of your service on a per-customer or per-user basis
  • Add instrumentation to frequently called code paths, without impacting performance or overwhelming external analytics systems with events

Cloudflare uses Analytics Engine internally to store and product per-product metrics for products like D1 and R2 at scale.

To get started with Analytics Engine:

Vectorize

Vectorize is a globally distributed vector database that enables you to build full-stack, AI-powered applications with Cloudflare Workers and Workers AI.

Vectorize allows you to:

  • Store embeddings from any vector embeddings model (Bring Your Own embeddings) for semantic search and classification tasks.
  • Add context to Large Language Model (LLM) queries by using vector search as part of a Retrieval Augmented Generation (RAG) workflow.
  • Filter on vector metadata to reduce the search space and return more relevant results.

To get started with Vectorize:

SQL in Durable Objects vs D1

Cloudflare Workers offers a SQLite-backed serverless database product - D1. How should you compare SQLite in Durable Objects and D1?

D1 is a managed database product.

D1 fits into a familiar architecture for developers, where application servers communicate with a database over the network. Application servers are typically Workers; however, D1 also supports external, non-Worker access via an HTTP API ↗︎, which helps unlock third-party tooling support for D1.

D1 aims for a "batteries included" feature set, including the above HTTP API, database schema management, data import/export, and database query insights.

With D1, your application code and SQL database queries are not colocated which can impact application performance. If performance is a concern with D1, Workers has Smart Placement to dynamically run your Worker in the best location to reduce total Worker request latency, considering everything your Worker talks to, including D1.

SQLite in Durable Objects is a lower-level compute with storage building block for distributed systems.

By design, Durable Objects are accessed with Workers-only.

Durable Objects require a bit more effort, but in return, give you more flexibility and control. With Durable Objects, you must implement two pieces of code that run in different places: a front-end Worker which routes incoming requests from the Internet to a unique Durable Object, and the Durable Object itself, which runs on the same machine as the SQLite database. You get to choose what runs where, and it may be that your application benefits from running some application business logic right next to the database.

With SQLite in Durable Objects, you may also need to build some of your own database tooling that comes out-of-the-box with D1.

SQL query pricing and limits are intended to be identical between D1 (pricing, limits) and SQLite in Durable Objects (pricing, limits).

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