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Analytical queries on billions of rows
DatabasesFrom $29/app/month
Managed ClickHouse Hosting
Columnar database for real-time analytics
What is ClickHouse on ManageStacks?
ClickHouse on ManageStacks is production-grade ClickHouse deployed to your own AWS, Azure, or GCP region — priced flat at $29 per cluster per month regardless of query volume, with sub-second analytical queries on billions of rows, replication + sharding, materialized views, and native Kafka/S3 integrations. Materially cheaper than ClickHouse Cloud, Snowflake, or BigQuery for analytical workloads under 10 TB, and your analytical data stays in your cloud region.
ClickHouse on ManageStacks is production-grade ClickHouse deployed to your own AWS, Azure, or GCP region — priced flat at $29 per cluster per month regardless of query volume, with sub-second analytical queries on billions of rows, replication + sharding, materialized views, and native Kafka/S3 integrations. Materially cheaper than ClickHouse Cloud, Snowflake, or BigQuery for analytical workloads under 10 TB, and your analytical data stays in your cloud region.
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About ClickHouse
What ClickHouse does, and why teams deploy it.
ClickHouse is an open-source columnar database purpose-built for online analytical processing (OLAP). It executes analytical queries on billions of rows in milliseconds — an order of magnitude faster than row-based databases like Postgres or MySQL for group-by, filter, and aggregation workloads. That performance comes from three things: columnar storage (only read the columns you query), vectorised query execution, and aggressive compression (typical 10-100x reduction vs raw).
Originally built at Yandex for their web analytics platform, ClickHouse is now used at every scale — from log analytics on a few GB to petabyte-scale event pipelines at Cloudflare, Uber, and eBay. It supports full SQL (with analytical extensions), materialized views for pre-aggregated data, and native connectors for Kafka, S3, HDFS, PostgreSQL, MySQL, and Kinesis.
Running ClickHouse in production means running clickhouse-server, configuring MergeTree engines correctly (partition + primary key choice determines query performance), setting up ZooKeeper or ClickHouse Keeper for the replicated MergeTree family, sizing memory for query execution (ClickHouse loves RAM), and testing version upgrades (ClickHouse ships frequently — sometimes weekly). ManageStacks handles the operational side.
DIY vs ManageStacks
What running ClickHouse yourself looks like — and what it looks like with us.
DIY self-hosting
- Provision servers, install clickhouse-server, configure ClickHouse Keeper (or ZooKeeper)
- Design ReplicatedMergeTree topology and configure remote_servers.xml for cluster coordination
- Set up S3-backed backups; test restores; script backup retention
- Track ClickHouse's weekly releases and manually validate upgrades
- Size memory + max_memory_usage carefully; monitor query kill rates
On ManageStacks
- Subscribe through your AWS, Azure, or GCP marketplace
- ClickHouse comes up as a replicated cluster with Keeper coordination and Grafana monitoring
- S3-backed backups + retention run in the background
- Rolling upgrades across cluster nodes keep the database available
- Native Kafka + S3 + PG connectors ready to configure
ClickHouse on ManageStacks — key numbers
$29/mo
Flat per cluster, standard tier
10-100x
Compression ratios vs row-based databases
Kafka + S3
Native ingestion connectors built in
Key features
Everything ClickHouse ships with, running on our stack.
- Columnar storage with 10-100x compression vs row-based DBs
- Sub-second analytical queries on billions of rows
- Full SQL + analytical extensions (window functions, arrays, tuples, nested types)
- Materialized views for real-time pre-aggregation
- Native integrations: Kafka, S3, HDFS, PostgreSQL, MySQL, Kinesis, MongoDB
- Distributed engine with ReplicatedMergeTree + sharding
- ClickHouse Keeper (Raft-based, ZooKeeper-compatible) for coordination
- Approximate queries (uniqHLL12, quantileTDigest) for interactive-latency analytics
- Prometheus-exporter metrics + Grafana dashboards included
- Full data export — table dumps, backup engine, or S3-backed backups
How it deploys
From subscribe to live in minutes.
Subscribe
Subscribe to ManageStacks through your AWS, Azure, or GCP marketplace.
Provision
ClickHouse replicated cluster spins up with Keeper coordination, S3-backed backups, and Grafana monitoring — typically 3-5 minutes.
Load data
Ingest from Kafka, S3, Postgres, or via INSERT SELECT from remote(). Design MergeTree tables with the right partition + primary key for your queries.
Query
Point Superset, Grafana, dbt, or your BI tool at the cluster. Dashboards refresh in milliseconds, not seconds.
Who this is for
Built for teams that want ClickHouse to just work.
Product analytics + event pipelines
You're ingesting millions of events daily (page views, user actions, ML feature logs). Postgres slows down at scale; Snowflake is expensive for high-frequency queries. ClickHouse is purpose-built for this.
Log + observability platforms
You want to keep logs in your cloud for compliance and cost. ClickHouse + Grafana + Loki is the modern OSS observability stack.
Embedded analytics in SaaS
You're rendering per-customer dashboards in your app. Snowflake per-query cost breaks the unit economics; ClickHouse's flat-priced dedicated model doesn't.
Compliance & compatibility
What we handle, what ClickHouse runs on.
Compliance & operations
- TLS-encrypted connections + inter-node communication
- S3-backed backups encrypted and stored in a separate region
- OS-level and ClickHouse security patches applied during your maintenance window
- GDPR data-residency — cluster stays in your chosen cloud region
- Row-level and column-level access control via ClickHouse's RBAC
- Audit logging on query activity retained per your compliance window
Compatibility
- Version
- Latest ClickHouse LTS or stable — pin your major version
- Runtime
- clickhouse-server on containerised infrastructure
- Dependencies
- ClickHouse Keeper (Raft-based) for coordination; S3 for backups
- Min. resources
- 4 vCPU / 8 GB RAM (dedicated) — analytical queries love RAM
How ManageStacks helps
We handle the parts you shouldn't be writing yourself.
ManageStacks handles the operational complexity of production ClickHouse — replicated cluster setup, ClickHouse Keeper for coordination, S3-backed backups, memory tuning for query execution, and version upgrades tested against your data — so your data team focuses on schema design, MergeTree engine choice, and materialized-view topology instead of the operating platform.
How it compares
ClickHouse on ManageStacks vs the alternatives.
How ClickHouse on ManageStacks compares to ClickHouse Cloud and the two dominant cloud data warehouses for analytical workloads.
| Property | ClickHouse on ManageStacksUs | ClickHouse Cloud | Snowflake | Google BigQuery |
|---|---|---|---|---|
| Deployment | Managed on your AWS, Azure, or GCP | Vendor-hosted (multi-cloud) | Vendor-hosted | GCP-managed |
| Data residency | Your cloud region | Vendor region choice | Vendor region choice | GCP region |
| Pricing basis | Flat per cluster | Per compute-unit + storage + queries | Per credit-second + storage | Per byte-scanned + storage |
| Compute model | Dedicated compute | Serverless / autoscaling | Serverless warehouses | Serverless |
| Open source | Yes (Apache 2.0) | Yes (Apache 2.0, hosted) | No (proprietary) | No (proprietary) |
| Best for | High-QPS embedded analytics, event pipelines | Elastic workloads, hands-off ops | Ad-hoc BI, data sharing | Ad-hoc queries, sporadic workloads |
Comparison focuses on architectural properties (deployment model, pricing basis, open-source status) that don't change with vendor pricing pages. Verify current pricing on each vendor's own site.
FAQ
Common questions about ClickHouse on ManageStacks.
How does this compare to ClickHouse Cloud?
ClickHouse Cloud is the vendor-hosted offering, priced per compute-unit + storage + queries. ManageStacks is a flat $29 per cluster at standard tier. For workloads under 10 TB and moderate query concurrency, self-hosted on ManageStacks is materially cheaper. ClickHouse Cloud is worth it for very-large fleets, serverless auto-scaling, or if you specifically want the vendor's roadmap features (SharedMergeTree, etc).
How does this compare to Snowflake or BigQuery?
Different tradeoff. Snowflake and BigQuery are serverless — you pay per query-second or per byte-scanned, with elastic scaling. ClickHouse on ManageStacks is dedicated infrastructure at flat price — you get the compute you provisioned, with predictable cost. For high-query-volume analytical workloads (dashboards refreshing every minute, user-facing embedded analytics), ClickHouse's dedicated model is often cheaper. For sporadic ad-hoc analysis, serverless wins.
How is ClickHouse replication set up?
ReplicatedMergeTree tables replicate automatically via ClickHouse Keeper (or ZooKeeper). Standard plans include a 2-node replicated cluster; Business+ plans include multi-shard clusters for horizontal write scale. Replicated tables survive node failures without data loss.
Can I stream data in from Kafka?
Yes — Kafka is a first-class ingestion source. ClickHouse's Kafka engine consumes from topics and lands into MergeTree tables (usually via a materialized view for schema shaping). If Kafka is also on ManageStacks, the two run in the same cloud region — no cross-region data transfer.
Does ManageStacks handle ClickHouse version upgrades?
Yes. ClickHouse ships weekly stable releases. We track LTS versions and validate upgrades against a clone of your data before rolling forward. Rolling upgrades across replicated cluster nodes keep the database available throughout.
How is backup handled — ClickHouse's own backup engine or something else?
ClickHouse's native BACKUP / RESTORE commands (with S3 destination) are used for full and incremental backups. Daily backups are encrypted and stored in a separate region. Point-in-time recovery within the retention window is available.
What about materialized views and Refreshable Materialized Views?
Standard materialized views (populate synchronously as data lands) work as documented. Refreshable Materialized Views (periodic full or incremental refresh) are supported on recent ClickHouse versions and available on ManageStacks.
What happens if I want to migrate off?
Full backup export via ClickHouse BACKUP command (self-describing format, portable to any ClickHouse deployment). Or use clickhouse-copier / remote() table function for direct migration to another cluster. ClickHouse is Apache-2.0 licensed and portable. Migration off is a supported operation.
Deploy ClickHouse in under 5 minutes.
Subscribe through your AWS, Azure, or GCP marketplace. We handle provisioning, SSL, monitoring, backups, updates, and security. From $29/app/month.