Choosing between managed ClickHouse services means deciding how much abstraction you want between your application code and the database. ClickHouse Cloud gives you a hosted database on cloud infrastructure with direct access to configure and query as you see fit, while Tinybird wraps ClickHouse in a developer experience that handles infrastructure and exposes a more limited set of database controls.
Lets compare how both Tinybird and ClickHouse Cloud handle database operations, ingestion, pricing, and development workflows so you can figure out which cloud-based managed ClickHouse best fits your team structure and use case.
Problems managed ClickHouse services solve
Running ClickHouse yourself is pretty hard, even for experienced DBAs. ClickHouse is a highly-scalable database designed to run on distributed nodes, which means configuring clusters, setting up replication, automating backups, and tuning queries for performance. Depending on your experience level, setup tasks can take weeks or months of work before you actually start data modeling or building features.
Managed ClickHouse services handle the infrastructure so you can focus on data modeling, query writing, and shipping analytics features. Both ClickHouse Cloud and Tinybird remove the operational burden of actually maintaining the database cluster, but they take different approaches to abstraction and developer workflow.
Tinybird and ClickHouse Cloud at a glance
ClickHouse Cloud is the managed ClickHouse service offered by ClickHouse, Inc. With ClickHouse CLoud you get hosted ClickHouse clusters with direct database access using standard clients like JDBC, ODBC, or the native protocol.
Tinybird is a developer platform built on ClickHouse that abstracts the database moreseo than ClickHouse. Instead of connecting to the underlying ClickHouse database directly, you generally define data pipelines as code and deploy SQL queries as REST API endpoints. (Note that Tinybird does expose read access to the underlying ClickHouse database via a native HTTP interface)
| Feature | ClickHouse Cloud | Tinybird |
|---|---|---|
| Target user | Database administrators, data engineers, mature devops teams | Software developers, founding engineers, enterprise teams that want to move faster |
| Access method | Database clients (JDBC, ODBC, HTTP) | REST APIs with tokens, SQL API, HTTP interface |
| Infrastructure control | Manual cluster configuration | Limited cluster ops, automatic scaling |
The core difference is abstraction level. ClickHouse Cloud gives you a managed database that you configure and query yourself, while Tinybird handles database operations and exposes access primarily via API, including Tinybird's APIs and the API endpoints that you create within Tinybird.
Infrastructure and operations comparison
Cluster provisioning and autoscaling
ClickHouse Cloud requires you to select cluster sizes and configure scaling policies. You can scale vertically by changing instance types or horizontally by adding replicas, but planning and executing these changes takes time.
Tinybird abstracts cluster management completely. The platform monitors query patterns and scales compute automatically based on demand across customers on shared infrastructure, without requiring you to configure anything except your vCPU tier.
Upgrades and backups
ClickHouse Cloud provides automated backups and lets you schedule maintenance windows for version upgrades. You decide when to upgrade to new ClickHouse versions, which gives you control but means tracking release notes and planning migration timing.
Tinybird handles upgrades transparently as part of the managed service. Backups run automatically, and upgrades are handled by Tinybird on an cluster-by-cluster basis.
Observability and alerting
ClickHouse Cloud exposes system tables and metrics about query performance, storage usage, and cluster health. Setting up dashboards and alerts requires exporting these metrics to external monitoring tools.
Tinybird includes application-level observability by default. Every API endpoint tracks request latency, error rates, and query performance automatically. Tinybird includes built-in observability dashboards as well as queryable service data sources that maintain API and ingestion logs.
Ingestion, integration, and API capabilities
Streaming connectors
ClickHouse Cloud connects to Kafka clusters using the Kafka table engine. You write the integration code yourself, handling authentication, schema mapping, and error handling. ClickHouse Cloud also includes some native data source connectors, called "ClickPipes".
Most developers use Tinybird's native HTTP streaming endpoint, /v0/events, to ingest. The endpoint accepts up to 1,000 req/s and 20 MB/s and handles load balancing, backpressure management, and database writes without requiring custom code or additional infrastructure. Tinybird also provides native connectors for Kafka, S3, and GCS as well as guided ingestion configurations for 50+ different data sources
Popular Tinybird connectors and integrations:
- Kafka with Schema Registry support
- AWS S3
- Google Cloud Storage
- AWS DynamoDB
- AWS Kinesis
- Google Cloud Pub/Sub and BigQuery via GCS
- Snowflake via S3
- CDC for Postgres and MongoDB
Querying and table creation
ClickHouse Cloud gives you a SQL editor to write SELECT and DDL queries. This allows you to create tables using standard CREATE TABLE queries. It also gives you direct control over creating materialized view definitions and refresh strategies.
Tinybird adds "data sources" and "pipes" as a higher-level abstraction for data transformations. Rather than creating resources via SQL, you define connections, data sources, and queries as plaintext files. A data source includes a ClickHouse table definition as well as connector metadata. A pipe is a SQL query that reads from data sources or other pipes, creating a chain of transformations that Tinybird combines and optimizes automatically.
Pipes can be deployed as API endpoints, sinks, materializations, or serverless copy functions
API layer
Tinybird's most notable abstraction is its API endpoint layer. Every SQL query (pipe) can be published and deployed as an API endpoint. Tinybird hosts, secures, and scales your API, preventing the need to build additional infrastructure for common query patterns exposed as endpoints.
ClickHouse Cloud requires you to build your own API layer. This typically means writing backend code that accepts HTTP requests, constructs SQL queries, executes them against ClickHouse, and returns formatted responses.
Tinybird generates REST APIs automatically from SQL queries. You write a SQL query with parameters, and Tinybird deploys it as an authenticated HTTP endpoint that returns JSON.
Here's an example Tinybird endpoint pipe:
TOKEN analytics_read READ
NODE endpoint
SQL >
SELECT
%
user_id,
count() as event_count
FROM events
WHERE event_type = {{ String(event_type, 'pageview') }} --query parameter syntax
AND timestamp >= {{ DateTime(start_date) }}
GROUP BY user_id
ORDER BY event_count DESC
LIMIT {{ Int32(limit, 100) }}
TYPE endpoint --will publish as API when deployed
This single file defines the SQL logic, query parameters with defaults, and access control, then deploys as an API that your application calls with any standard HTTP requests library.
Performance and concurrency benchmarks
Typical latency under load
Both platforms deliver sub-second query latency for analytical workloads based on the compute resources allocated to your cluster.
ClickHouse Cloud performance depends on the cluster configuration you choose. Larger instances and more replicas handle higher concurrency. In Tinybird, you select a vCPU plan that matches your latency and concurrency needs. Both platforms include some amount of automatic scaling. ClickHouse charges based on active compute hours and does not bill for idle periods, so your final bill depends on cluster size and active compute time. Tinybird's pricing is plan-based, so costs tend to be more stable and predictable within plan limits.
Vector search and AI workloads
ClickHouse supports vector operations through functions like cosineDistance() and L2Distance(), which work in both ClickHouse Cloud and Tinybird. You store embeddings as Array(Float32) columns and compute similarity scores in SQL.
Both ClickHouse Cloud and Tinybird offer hosted MCP servers for connecting LLMs and AI agents for read access to data. Tinybird's MCP server also exposes API endpoints as tools - and has a few other tools for exploratory data analysis.
Tinybird also offers a suite of AI tooling for creating and optimizing resources and exploring data.
Pricing models and cost predictability
Compute and storage charges
ClickHouse Cloud bills based on compute hours (measured in vCPU time) and storage volume (measured in GB). You can stop services when not in use to avoid compute charges, but this adds manual overhead and doesn't work for applications that need continuous availability.
Tinybird uses plan-based pricing that bundles compute, storage, and API requests into monthly tiers. Compute scales automatically within your plan limits, so you don't pay separately for CPU time.
Data transfer and egress fees
ClickHouse Cloud charges variable egress rates depending on the source and destination regions. Cross-region replication or querying data from different availability zones can add unpredictable costs.
Tinybird includes data transfer in plan pricing with a two-tier model: transfers within the same cloud provider region are significantly less expensive than cross-region transfers; both have a fixed per-GB rate.
Free tier limits
ClickHouse Cloud does not offer a free plan, but they do offer $300 in trial credits that expire after 30 days. Once credits run out, you start paying for compute and storage at standard rates.
Tinybird provides a permanent free tier with 10 GB storage, 0.5 vCPU compute, and 1,000 API requests per day. This free tier doesn't expire, making it useful for prototyping or running small production workloads indefinitely.
Developer workflow and tooling differences
Local dev and CI/CD
ClickHouse Cloud requires managing database connections and credentials when developing locally. You typically connect to a remote cluster, which means your local development depends on network access.
Tinybird provides a CLI and a local Tinybird instance that runs in Docker, allowing you to develop and test data projects offline. You can define data sources, write SQL queries, and test APIs locally alongside application code before deploying to production.
The typical Tinybird workflow looks like this:
tb local start # Start the local container
tb create # Create project structure and metadata
tb dev # Builds with hot reload on change
tb datasource create events # Define a data source
touch analytics.pipe # Create a SQL pipe
tb --cloud deploy # Deploy
# or git add . && git commit -m "tinybird" && git push origin
# Run tests + check and handle deployments in CI/CD
Access control and tokens
ClickHouse Cloud uses database users and roles with SQL-based permissions. You grant privileges on specific tables or databases, and applications connect using usernames and passwords. Access the database from the application typically requires that you build a database API proxy.
Tinybird generates API tokens with fine-grained permissions scoped to specific pipes or data sources. Tokens can be read-only or read-write, and you can create separate tokens for different applications without managing database users. Tinybird also supports JWTs with row-level security policies - useful for accessing Tinybird resources directly from the frontend without the need for a database API proxy.
SDKs and client libraries
ClickHouse Cloud works with standard ClickHouse client libraries in Python, Go, Java, Node.js, and other languages. The clients speak the native ClickHouse protocol and give you full access to database features.
Tinybird provides REST APIs that work with any HTTP client, meaning you can use fetch() in JavaScript, requests in Python, or curl from the command line without installing database-specific drivers. In addition, Tinybird offers an SQL API that you can use within application code, or you can use the same ClickHouse client libraries as ClickHouse Cloud via Tinybird's native HTTP interface.
Security, compliance, and multi-region options
Data residency controls
Both platforms offer multi-region deployment across AWS and Google Cloud. ClickHouse Cloud supports 25 cloud regions, additionally supports Azure, and - like Tinybird - requires you to select regions when creating services and manage cross-region replication yourself if needed.
SOC 2 and ISO certifications
ClickHouse Cloud maintains SOC 2 Type II certification and provides compliance documentation for enterprise customers. Audit logs and access controls help meet regulatory requirements.
Tinybird maintains SOC 2 Type II and HIPAA certifications and provides similar compliance features as ClickHouse Cloud.
Private networking options
ClickHouse Cloud supports VPC peering and AWS PrivateLink for secure connectivity from your infrastructure to managed clusters. Setting up private networking requires configuring network routes and firewall rules on both sides.
Tinybird also offers VPC peering and AWS PrivateLink for enterprise plans, allowing your applications to access APIs through private network connections without exposing them to the public internet.
When to choose Tinybird or ClickHouse Cloud
Rapid-iteration product teams
Tinybird fits teams building user-facing analytics who want to ship features quickly. If your goal is exposing real-time data through APIs in your application, Tinybird's abstraction layer removes the work of building and maintaining that API layer yourself.
The platform works well when you value developer velocity over database-level control, and when your team prefers defining infrastructure as code rather than configuring clusters through a UI.
Heavy in-house DBA / DevOps expertise
ClickHouse Cloud suits organizations with database administration resources who need granular control over cluster configuration, query optimization, and performance tuning. If you already have team members who understand ClickHouse internals and want direct access to system tables and settings, ClickHouse Cloud provides that flexibility.
This option makes sense when you're migrating existing ClickHouse workloads to a managed service but want to maintain your current operational practices.
Build faster with Tinybird
Tinybird removes the infrastructure work that typically slows down ClickHouse work. Instead of spending weeks setting up clusters, building ingestion pipelines, and creating API layers, you can deploy your first real-time analytics API in a few hours (tops).
Sign up for a free Tinybird account to start building real-time analytics APIs. The free tier includes 10 GB storage and 1,000 daily API requests, with no credit card required and no expiration date.
FAQs about Tinybird vs ClickHouse cloud
How do I migrate from ClickHouse Cloud to Tinybird?
Export your data using ClickHouse native formats like Parquet or NDJSON, then create Tinybird data sources and upload the files through the CLI or UI. You'll rewrite your queries as Tinybird pipes, which means adding parameter definitions and specifying which queries become API endpoints.
Can I run Tinybird in my own virtual private cloud?
Tinybird operates as a fully managed service but also offers self-managed regions for single-node deployments. ClickHouse Cloud offers Bring Your Own Cloud (BYOC) options for enterprise customers who need to run the service within their own AWS or Google Cloud accounts. Of course you can always self-host OSS ClickHouse as well.
Does Tinybird support vectors and hybrid search?
Yes, Tinybird supports vector operations using ClickHouse's distance functions like cosineDistance() and L2Distance(). The platform provides optimized indexing for combining vector similarity with traditional filtering, which helps when building recommendation or semantic search features.
What happens to my data if I exceed my plan limits?
Tinybird continues serving requests but may throttle API response times or queue ingestion when you exceed plan limits. You can upgrade to a higher tier at any time, and the platform provides usage alerts before you hit limits.
Can I use Tinybird with existing Kafka streams?
Yes, Tinybird's native connectors support Kafka, including Confluent Cloud and other Kafka providers. You configure the connector through the UI or CLI by providing connection details and authentication credentials, and Tinybird handles schema inference and continuous ingestion automatically. Tinybird also offers a native HTTP streaming endpoint for those who do not have or do not want to set up streaming infrastructure.
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