Best managed clickhouse service in 2025

Introduction

ClickHouse is an open-source, column-oriented SQL database management system designed for online analytical processing (OLAP) and real-time analytics. Initially developed by Yandex, it excels at rapid query execution on massive datasets, achieving millisecond-level response times even when processing billions of rows. This speed comes from its core architectural features like columnar storage, aggressive data compression, sparse indexing, and vectorized query execution. ClickHouse is highly versatile, deployable on-premises or in the cloud, with managed services available for simplified hosting. Its real-time performance and high-throughput ingestion make it perfect for various analytical tasks, including product analytics, observability platforms, IoT telemetry, and other large-scale real-time data processing needs.

Managed ClickHouse services offer significant advantages over self-hosting, primarily by reducing operational overhead as providers handle infrastructure, maintenance, and security, freeing your teams to focus on data analysis and development. They ensure high scalability and reliability through automatic replication, dynamic resource allocation, and robust backup solutions. Furthermore, these services can be more cost-efficient than self-hosting due to optimized resource utilization and predictable cost models. Finally, users benefit from enhanced support, gaining access to specialized ClickHouse experts for assistance and training. This why managed ClickHouse services are high in demand.

In this article, we will examine several managed ClickHouse services on the market. Our aim is not to find a single best provider, but instead to present you, the reader, with their offerings so you can make an informed decision.

Key Evaluation Parameters for Managed ClickHouse

Evaluating managed ClickHouse services requires a structured approach across several critical dimensions. The following parameters define the criteria used in this analysis:

Leading Managed ClickHouse Service Providers

Based on the available information, the following five services are identified as leading managed ClickHouse offerings or platforms built upon ClickHouse, representing diverse approaches to delivering high-performance analytics:

1. ClickHouse Cloud: The official managed service provided by ClickHouse, Inc.
2. Tinybird: A real-time analytics layer that facilitates the creation of production-grade APIs from SQL queries, built on open-source ClickHouse.
3. Altinity.Cloud: A fully managed ClickHouse service that maintains a 100% open-source core, distinguished by its support for Bring Your Own Cloud (BYOC) and Bring Your Own Kubernetes (BYOK) deployments.

The following table provides a high-level feature matrix for these leading managed ClickHouse services:

In-Depth Analysis of Top Managed ClickHouse Services

ClickHouse Cloud

ClickHouse Cloud is the official managed service offered by ClickHouse, Inc. It is designed to deliver the inherent speed and power of ClickHouse within a cloud environment, significantly reducing the operational burden of infrastructure management for users.

ClickHouse SQL Console Interface. Source: ClickHouse Cloud Website

Performance and Query Capabilities

ClickHouse Cloud harnesses ClickHouse’s core strengths—columnar storage, superior compression, sparse indexing, and vectorized queries—delivering millisecond responses on billion-row datasets. Built for real-time analytics, it handles millions of rows per second and optimizes performance with native support for primary keys, skip indexes, and materialized views.

As the official managed service, ClickHouse Cloud offers the latest features with enterprise-grade reliability, including multi-zone replication and seamless upgrades. Ideal for organizations prioritizing stability and cutting-edge performance without managing infrastructure, it provides a streamlined, optimized experience.

Scalability & Elasticity

The service is designed for seamless scaling, automatically adjusting resources up or down to meet fluctuating workload demands, thereby eliminating the need for over-provisioning. A foundational aspect of its architecture is the decoupling of compute and storage resources, which are backed by an object store. This separation enables the independent scaling of each component, resulting in a superior price-to-performance ratio. Multi-level caching is employed to optimize performance further and efficiently manage data, thereby supporting overall scalability by reducing the need for frequent access to slower storage layers. The platform also includes integrated cost and scaling controls, as well as the absence of manual data sharding, which, combined with automatic replication, simplifies the scaling process for users.

Because storage and compute are decoupled and an object store backs it, ClickHouse Cloud can dynamically adjust resources, including scaling idle services to zero, which efficiently handles spiky workloads. This represents a substantial advantage over traditional, tightly coupled deployments, directly translating into cost savings and operational simplicity for dynamic analytical demands.

Developer Experience

ClickHouse Cloud is engineered for a serverless and simple developer experience, aiming to minimize operational overhead and allow developers to concentrate on data insights. It offers a Terraform provider and comprehensive APIs for automating setup and configuration, which promotes consistency and efficiency across deployments. An exclusive interactive SQL console is available to ClickHouse Cloud customers, providing a user-friendly interface for connecting, exploring, and querying databases. This console features include an easy-to-use table explorer, a powerful query interface, and a data ingestion wizard. The platform also supports a wide array of data connectors, visualization tools, SQL, and language clients.

The strong emphasis on effortless automation via Terraform and APIs, coupled with the intuitive interactive SQL console, indicates that ClickHouse Cloud targets developers who prefer programmatic and efficient management of their data and queries, without being encumbered by manual infrastructure tasks. The serverless nature and automatic replication further reinforce this focus, empowering developers to prioritize data insights and application logic.

Integration & Ecosystem

ClickHouse Cloud boasts a broad ecosystem support, facilitating seamless integration with various data connectors, visualization tools, SQL, and language clients. It also supports ingestion from Postgres and Vector. For data visualization, it integrates with popular tools such as Superset, Grafana, Tableau, Metabase, and Hex. Developers can utilize various programming languages, including Go, Python, Java, C++, and Node.js. Furthermore, its compatibility with the MySQL interface allows connections to any MySQL-compatible data tools. The ClickHouse community maintains an active presence across various platforms, including GitHub, Slack, LinkedIn, X, Telegram, and Meetup.

The extensive list of integrations, spanning ingestion, visualization, and language clients, demonstrates ClickHouse Cloud's ambition to serve as a central analytical database that integrates smoothly into diverse existing data ecosystems.

Pricing & Cost Efficiency

ClickHouse Cloud offers three tiers of pricing: Basic, Scale, and Enterprise. All of the offerings include storage at $25.30 per 1 TB per month and compute ranging from $0.2181 to $0.3903 per unit per hour.

You can also modify the compute resources, such as RAM and the number of vCPUs. The pricing philosophy centers on paying only for what is used, with automatic scaling of compute resources up and down based on workload, and the ability to scale unused resources down to zero, preventing charges for idle services.

The pay-only-for-what-you-use and scale-down-to-zero features are direct benefits of its decoupled architecture, enabling substantial cost savings during idle periods or low usage. This makes it an attractive option for organizations seeking to optimize cloud spend for analytical workloads, particularly those considering migration from more expensive or less flexible alternatives. Full information can be found on their pricing page.

Primary Target Audience

ClickHouse Cloud primarily targets developers who work with data at scale. It is ideal for organizations that desire deep customization and real-time analytics capabilities. This includes teams requiring ultra-low-latency performance for powering user-facing dashboards, monitoring systems, or product analytics at massive scale. It is also well-suited for users dealing with high ingest, high-volume streams such as logs, metrics, IoT streams, and raw telemetry. Furthermore, the "Bring Your Own Cloud (BYOC)" option caters to organizations with strict data residency and compliance requirements.

TinyBird

Tinybird is a real-time analytics layer built on top of open-source ClickHouse. Its primary focus is to empower developers to build analytical software features and transform SQL queries into production-grade APIs. It offers a higher level of abstraction compared to general-purpose managed ClickHouse services, simplifying many underlying database management details.

TinyBird Interface. Source: Tinybird Blog Post

Performance & Query Capabilities

Tinybird is powered by ClickHouse and claims great performance out of the box. It also demonstrates the ability to scale effectively to meet demand. It is specifically optimized for user-facing analytics use cases, where low latency and high concurrency are paramount. Tinybird supports streaming ingestion of thousands, or even millions, of events per second via HTTP or through a native Kafka connector. It boasts sub-second latency on datasets containing billions of events.

Tinybird's explicit focus on an "out-of-the-box tuned database cluster optimized for user-facing analytics use cases" highlights a specialized performance orientation. This indicates that Tinybird has made deliberate architectural and configuration choices to prioritize low-latency, high-concurrency queries, which are characteristic of interactive dashboards and applications, rather than general analytical workloads. This specialization provides a streamlined path for application developers to achieve specific performance goals for their data-driven features.

Scalability & Elasticity

Tinybird's hosted ClickHouse database is designed to scale seamlessly to manage varying demands. The service automatically handles database upgrades, reducing operational overhead for users. It supports high-volume data intake through streaming ingestion capabilities. The platform integrates with object storage sources and sinks, offering a native S3 connector to minimize the need for external ETLs and complex data pipelines. For large and recurring data tasks, it allows users to run scheduled sources, sinks, and copies using serverless asynchronous job queues. Tinybird also provides local and cloud runtimes, offering flexibility in deployment. Security features, such as securing resources with static tokens or scoped JWTs and supporting row-level security, ensure scalable access control. The service is SOC2 Type II certified and HIPAA compliant, providing a secure and compliant environment for scalable data operations.

Tinybird's approach to scalability extends beyond raw infrastructure capabilities, deeply integrating with its developer experience. Features like "data as code," Git-based CI/CD workflows, instant deployments and rollbacks, and live schema migrations enable developers to build and evolve scalable applications more rapidly and reliably. This indicates that Tinybird's scalability benefits are derived not only from its managed ClickHouse backend but also from its comprehensive tooling, which streamlines the development lifecycle for scalable data products.

Developer Experience

Tinybird offers a developer experience characterized by a higher level of abstraction compared to ClickHouse Cloud, abstracting away many of the finer details of database management. A key feature is the ability to publish any SQL query as a secure, performant, and parameterized OpenAPI REST API endpoint with a single click. It supports dynamic query parameters, automatically generates OpenAPI specifications, and allows securing APIs with custom JWTs. Full-service management is available via both API and CLI. The platform features robust Git integration for automated CI/CD workflows. Tinybird promotes a "data as code" philosophy, where table schemas and data pipelines are defined as plaintext files, enabling version control and collaborative development. Developers can perform local project validation with hot refreshes and conduct end-to-end testing, including building fixtures, testing data quality, and running unit tests during build and deploy processes. Deployments and rollbacks are instant and can be executed with a single command from the CLI. Furthermore, it supports AI-powered IDE integration and provides comprehensive documentation.

Tinybird's strong emphasis on one-click publish REST APIs from SQL queries and its data as code philosophy with Git integration clearly positions it as an API-first platform for application developers. This represents a significant shift from a traditional database management experience, suggesting that Tinybird aims to serve as the backend for applications that consume real-time analytics, rather than solely as a data warehouse for analysts. This specialized focus streamlines the process of programmatically exposing data insights, making it highly attractive for product teams building data-driven features.

Integration & Ecosystem

Tinybird integrates with dozens of development tools and data sources. For data ingestion, it supports Apache Kafka, Confluent Cloud, Redpanda, Google BigQuery, Snowflake, Postgres Table Function, Amazon DynamoDB, and Amazon S3. Its Events API facilitates streaming JSON data via HTTP, and it supports OpenTelemetry for real-time telemetry without extensive setup. For querying, it integrates with ClickHouse Client, DBeaver, JDBC Driver, Python Driver, Splunk DB Connect, and Splunk Hydrolix Search. Visualization tools supported include Apache Superset, Grafana, Kibana, and Redash. It also offers enrichment capabilities through ScientiaMobile WURFL. The Tinybird community is active on Slack and GitHub, and the platform showcases customer stories, a blog, videos, templates, and a newsletter.

The integrations offered by Tinybird, particularly for streaming data sources (Kafka, Kinesis, HTTP APIs) and tools for building data products (OpenTelemetry) , underscore its specialization in real-time user-facing analytics. The prominence of customer stories from companies building applications like Vercel, Canva, and FanDuel demonstrates a robust, use-case-driven ecosystem, rather than a general-purpose one.

Pricing & Cost Efficiency

Tinybird offers a "Free" tier that includes 0.5 vCPU, a maximum of 10 QPS, 10GB of storage, and 1,000 queries per day, along with Slack community support. The "Developer" tier is priced at $25 per month, providing 0.25 vCPU, 150 vCPU hours included (with overage charges), 25GB of included storage (with additional charges per GB), and data transfer costs. For larger enterprises, an "Enterprise" tier is available with custom pricing, dedicated infrastructure, credit-based billing, starting at 8 vCPUs and 1TB storage, and includes performance SLAs, support SLAs, and SSO.

The availability of a generous "Free" tier and an accessible "Developer" tier indicates a strategy designed to encourage developer adoption and experimentation. This land-and-expand approach is common for developer-focused tools, allowing users to test and build before committing to larger plans. The transition to a custom "Enterprise" tier for larger deployments suggests that scaling to mission-critical applications necessitates dedicated resources and tailored support, reflecting the increased value and complexity that come with that scale. This tiered pricing structure aligns well with its target audience of developers building data products.

Full pricing information can be found on their pricing page.

Primary Target Audience

Tinybird primarily targets developers and companies that need to build scalable, secure, real-time analytics APIs without complex upfront infrastructure projects. It is particularly well-suited for creating dashboards, internal tools, and data-driven applications that require real-time analytics. Product teams and engineering teams looking to integrate real-time analytics features into their applications efficiently represent a core audience.

Altinity.Cloud

Altinity.Cloud is a fully managed ClickHouse service that distinguishes itself by remaining 100% open source, offering users unique deployment flexibility through Bring Your Own Cloud (BYOC) and Bring Your Own Kubernetes (BYOK) options. Altinity is also a significant contributor to the broader ClickHouse ecosystem, actively maintaining various open-source tools.

Altinity Clusters Interface. Source: Altinity Documentation

Performance & Query Capabilities

Altinity.Cloud is designed to deliver faster queries, lower costs, and optimal performance. It aims to provide millisecond results with dedicated, high-performance environments. The service offers flexibility in deployment, allowing users to operate with any machine or storage type and to choose between any Altinity Stable Build or official ClickHouse version. Performance optimizations include the fast addition and removal of shards and replicas, as well as vertical and horizontal scaling capabilities, and storage configurations optimized for I/O bandwidth. It also provides built-in displays to check compression efficiency and a query log to track recent and slow queries.

Unlike ClickHouse Cloud, Altinity.Cloud's emphasis on being 100% open source and allowing the use of any Altinity Stable Build or official ClickHouse version caters to users who value the ability to maintain specific ClickHouse versions or leverage Altinity's hardened builds. The provision of dedicated and high-performance environments suggests resource isolation for consistent performance, a critical factor for enterprise-level deployments.

Scalability & Elasticity

A key differentiator for Altinity.Cloud is its support for BYOC (Bring Your Own Cloud) and BYOK (Bring Your Own Kubernetes) deployments. This model provides managed support while allowing users to retain complete control over their underlying infrastructure. Users have the flexibility to scale ClickHouse clusters up and down quickly, as well as to assess different configurations of compute, memory, and storage. The service optimizes costs by separating compute and storage on a scalable basis. It ensures resource isolation by providing per-tenant Kubernetes environments. For high availability, ClickHouse replicas are spread across multiple availability zones, and the service supports rolling upgrades and automatic backups to ensure robust disaster recovery capabilities.

The BYOC and BYOK options represent a significant architectural choice. This indicates that Altinity.Cloud targets organizations with specific compliance, data residency, or existing infrastructure requirements that a pure SaaS model cannot meet. It offers the advantages of managed services, such as 24/7 support and automation, while granting customers control over their cloud infrastructure and Kubernetes environments. This hybrid approach to scalability appeals to more mature or regulated enterprises seeking a balance between operational ease and infrastructure control.

Developer Experience

Altinity.Cloud is designed to be ideal for developers who aim to leverage the full power of data on Kubernetes. It integrates seamlessly with GitOps practices, including tools like ArgoCD and Terraform. The platform also supports observability by providing Prometheus and Grafana templates. The Altinity Cloud Manager (ACM) offers a user-friendly interface with features such as a cluster launch wizard, a rescale wizard, comprehensive dashboards, a query explorer, and schema management tools. Extensive documentation is available, including quick start guides, user guides, administrator guides, and a dedicated API guide.

The explicit mention of "GitOps with ArgoCD and Terraform" and the ability to "fully exploit capabilities of AWS EKS, Google GKE, and Azure AKS" points to a strong emphasis on a DevOps-centric developer experience, particularly for teams already invested in Kubernetes. This indicates that Altinity.Cloud is not merely a managed database but a solution deeply integrated into modern infrastructure-as-code and container orchestration workflows, empowering developers and operations teams who manage their infrastructure programmatically.

Integration & Ecosystem

Altinity.Cloud operates across various cloud providers, including AWS, GCP, Azure, and Hetzner regions. It integrates quickly with other cloud-based services, ranging from data ingestion to business intelligence tools. As a major contributor to the ClickHouse ecosystem, Altinity maintains crucial open-source tools such as the Kubernetes Operator for ClickHouse, Altinity Stable Builds, and Altinity Backup tools. The service offers integrations with Datadog for logs, Grafana Cloud, Prometheus, and Loki for observability. It also supports integration with business intelligence tools like Superset and Tableau. Furthermore, Altinity provides guidance on integrating with event streams such as Kafka, RedPanda, and Pulsar, as well as various client libraries.

Altinity's role as a "major contributor to the ClickHouse ecosystem" is a powerful differentiator. This signifies that Altinity not only provides a managed service but actively shapes the open-source project, potentially leading to faster adoption of new features or more robust support for complex use cases. Their BYOC/BYOK model, combined with integrations for specific cloud services (EKS, GKE, AKS) and observability tools (Prometheus, Grafana), demonstrates a deep commitment to integrating with existing enterprise cloud infrastructure and open-source tooling.

Pricing & Cost Efficiency

Altinity Cloud provides two distinct pricing models for its managed ClickHouse service, designed to cater to different user needs and infrastructure preferences.

The first model, Managed service in Altinity's Cloud, operates on an on-demand basis, meaning users are charged solely for the resources they consume. Under this model, there are no hourly fees for servers or vCPUs, and storage is provided at no monthly cost. This comprehensive service includes 24/7 Elite Support and dedicated design assistance, ensuring users receive extensive guidance and help. Furthermore, there are no additional charges for network transfer fees. For organizations with larger or more consistent needs, Altinity also offers volume and reserved pricing options, details of which can be obtained by contacting them directly.

The second model, Managed service in your own cloud (BYOC - Bring Your Own Cloud), also follows an on-demand structure. This option grants users the flexibility to leverage their existing cloud credits and maintain full control over their cloud infrastructure. While the core principle of paying only for usage remains, specific pricing for this model varies slightly across different cloud providers, including AWS, Google Cloud Platform (GCP), Azure, and Hetzner. Across all these platforms, the hourly price per server is a consistent $0.347. However, the hourly price per vCPU differs, costing $0.0625 for AWS, GCP, and Azure, and a slightly lower $0.0347 for Hetzner. Importantly, monthly storage costs are free across all listed BYOC providers. Similar to the in-Altinity-cloud model, this service also encompasses 24/7 Elite Support and design assistance, with no network transfer fees. Volume and reserved pricing are also available for those opting for the BYOC model.

Full pricing information can be found in their pricing page.

Primary Target Audience

Altinity.Cloud is ideal for developers who want to run open-source ClickHouse anywhere, whether in their own cloud or Altinity's, and require 24/7 support for building and scaling applications. It caters to organizations that prioritize 100% open-source solutions with no feature restrictions. A significant target audience includes users who need Bring Your Own Cloud (BYOC) or Bring Your Own Kubernetes (BYOK) deployments for greater infrastructure control, data residency requirements, or to leverage lower-cost alternatives, such as Hetzner Cloud. It is also well-suited for enterprises seeking managed support while retaining complete control over their underlying infrastructure, as well as for teams with a strong DevOps and Kubernetes culture that utilize GitOps workflows.

Choosing the Right Service for your Use Case

Selecting the optimal managed ClickHouse service hinges on a clear understanding of your organization's specific needs, technical capabilities, and strategic objectives. Each service analyzed offers distinct advantages tailored to different scenarios:

• For General-Purpose Real-Time Analytics and Operational Simplicity:

  Choose ClickHouse Cloud if your priority is a fully managed, official ClickHouse experience with robust reliability, seamless scaling, and transparent pricing. It's ideal for developers who want to focus on data insights rather than infrastructure management, and for organizations with broad real-time OLAP needs, including user-facing dashboards, monitoring, and product analytics at scale. Its BYOC option also suits those with strict data residency requirements.

• For Building User-Facing Analytics and Data Products:

  Opt for Tinybird if your goal is to rapidly develop and deploy real-time analytics APIs for applications. This service is designed for developers who need to transform SQL queries into production-grade API endpoints with minimal effort, abstracting away much of the underlying database complexity. It's particularly strong for interactive dashboards and data-driven features within applications.

• For Enterprises Requiring Open-Source Control and Hybrid Cloud Deployments:

  Consider Altinity.Cloud if your organization values a 100% open-source ClickHouse core and requires flexibility in deployment, such as Bring Your Own Cloud (BYOC) or Bring Your Own Kubernetes (BYOK). This service is well-suited for enterprises with existing Kubernetes investments, strong DevOps cultures, or specific compliance needs that necessitate retaining control over their infrastructure while still benefiting from managed support.

By carefully evaluating these distinctions against your specific use case, technical team's strengths, and budgetary considerations, you can make an informed decision to select the managed ClickHouse service that best aligns with your strategic objectives.

Getting Data into Managed ClickHouse Services

Once you decide which service to use based on your use case, you still need to think about how to get data into the service. That is why we build GlassFlow.

GlassFlow is a real-time stream processor specifically designed to simplify the creation and management of data pipelines, particularly between Kafka and ClickHouse. It functions as a low-code transformation engine, enabling data engineers to build robust, real-time data systems with minimal configuration.

Key Ingestion Capabilities:

• Built-in Kafka Connector: GlassFlow offers seamless integration with Kafka clusters, automatically extracting data from Kafka topics. It supports multiple Kafka topics and partitions and has native support for JSON data types, eliminating the need for manual data pulling.
• Optimized ClickHouse Sink: It provides a native connection to ClickHouse for maximum performance during data ingestion. Users can configure batch sizes and adjustable wait times for optimal throughput. It also includes built-in retry mechanisms, automatic schema detection and management, and full support for JSON data types in ClickHouse.
• Streaming Deduplication: GlassFlow can perform real-time deduplication of Kafka streams before data is ingested into ClickHouse. This feature is configurable with time windows up to 7 days and simple setup for deduplication keys, preventing duplicate data from reaching ClickHouse.
• Temporal Stream Joins: The tool allows for real-time joining of two Kafka streams. These joins are configurable with time windows up to 7 days, simplifying the process of producing joined streams ready for ClickHouse ingestion.
• Low-Code Transformation Engine: Developers can write Python functions to specify data transformations, with GlassFlow handling the underlying infrastructure, including automatic scaling and low latency.
• Broad Source Integration: Beyond Kafka, GlassFlow seamlessly integrates with other data sources like Google Pub/Sub and AWS Kinesis.

GlassFlow is positioned as an ideal tool for Python developers seeking to streamline event-driven data pipelines, enhancing productivity and efficiency in real-time analytics scenarios such as user click tracking, IoT analytics, behavioral tracking, and fraud detection.

Conclusion

The landscape of managed ClickHouse services offers a diverse set of solutions, each tailored to different organizational needs and technical preferences. While all services leverage ClickHouse's foundational strengths in high-speed OLAP, their architectural choices and feature sets create distinct value propositions.

Indeed, there is no one-size-fits-all tool; the optimal choice depends entirely on your specific use case. For instance, if your primary need is a general-purpose, robust real-time OLAP database with official support and simplified operations, ClickHouse Cloud stands out. However, if your focus is on building user-facing analytics and rapidly exposing data insights via APIs, Tinybird provides a highly specialized and efficient pathway. Organizations with stringent compliance requirements or a strong DevOps culture favoring hybrid cloud deployments will find Altinity.Cloud's BYOC/BYOK options particularly appealing.

Furthermore, once you have set up your chosen managed service, a critical next step is getting your data efficiently and reliably into the service. For this crucial ingestion phase, we recommend you to try GlassFlow. It is a great service that excels in stream processing and integration, particularly for Kafka-to-ClickHouse pipelines. GlassFlow simplifies complex real-time data ingestion by offering built-in Kafka and optimized ClickHouse connectors, ensuring high-performance data delivery. Its standout features include real-time deduplication of Kafka streams, preventing redundant data from reaching your ClickHouse instance, and temporal stream joins, allowing you to combine data from multiple streams on the fly within configurable time windows. Moreover, its Python-based transformation engine empowers developers to define sophisticated data processing logic with simple Python functions, abstracting away the complexities of underlying streaming infrastructure. GlassFlow's serverless and event-driven architecture ensures automatic scaling and low latency, making it an ideal choice for building robust and efficient real-time data pipelines into your managed ClickHouse environment.