CrateDB Cloud
CrateDB Cloud is a fully managed, distributed database service that combines time-series, JSON, relational, vector, full-text, and geospatial data models into a single SQL-accessible engine.
Publisher review
CrateDB Cloud is a fully managed, distributed database service that combines time-series, JSON, relational, vector, full-text, and geospatial data models into a single SQL-accessible engine. It is operated by the team that built CrateDB, making it a strong fit for teams that need production-grade real-time analytics without a dedicated DBA or infrastructure crew. The service runs natively on AWS, Azure, or GCP, with deployment in under a minute and no manual provisioning. It targets organizations that have outgrown PostgreSQL for analytical workloads but want to avoid the operational complexity of self-managing a distributed system.
CrateDB Cloud handles the entire database lifecycle automatically: elastic scaling adds nodes or increases compute without downtime, zero-downtime upgrades apply new releases without a maintenance window, and automated backups run hourly on Dedicated plans (daily on Shared) with point-in-time restore. Built-in monitoring tracks cluster health, query performance, and resource utilization without requiring an external observability stack. The SQL Scheduler and table policies automate recurring tasks like data expiry, aggregation, and compaction. Dedicated plans support up to 9 nodes, 144 vCPUs, and 495 GB RAM, and the platform includes automatic sharding, rebalancing, and replication. Data is auto-indexed on ingest, enabling millisecond queryability for real-time pipelines.
Compared to ClickHouse, CrateDB Cloud trades some raw analytical throughput on purely structured data for multi-model flexibility—native vector search, dynamic schema, and unified full-text search are built in, not bolted on. ClickHouse requires manual tuning of table engines, shard keys, and merge tree configurations, while CrateDB Cloud automates sharding and rebalancing. TimescaleDB, another competitor, is optimized for time-series on top of PostgreSQL but lacks CrateDB Cloud's native support for JSON, vector, and geospatial data in a single engine. CrateDB Cloud also supports the PostgreSQL wire protocol, making it compatible with existing Postgres tooling.
The honest trade-offs: CrateDB Cloud's operational simplicity can come at the cost of less fine-grained control compared to ClickHouse's tunable columnar engine. Its vector search capabilities are native but currently limited for large-scale AI workloads that require dedicated vector databases. Some users report that CrateDB requires more tuning for peak performance on specific query patterns than ClickHouse. Finally, while the free tier is generous for development, production-scale Dedicated plans start at $0.246/hour, which can add up for clusters with many nodes.
How it works
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Fully managed operations
Deployment, scaling, patching, backups, and incident response are handled by the CrateDB engineering team, removing the need for a dedicated DBA.
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Multi-model data support
Handles time-series, JSON, relational, vector, full-text, and geospatial data within a single SQL-accessible engine.
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Automatic sharding and rebalancing
Data is automatically distributed across nodes, and the cluster rebalances itself when scaling up or down without downtime.
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Zero-downtime upgrades
New CrateDB releases are applied by the vendor without interrupting availability or requiring a maintenance window.
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Automated backups
Hourly backups on Dedicated plans, daily on Shared plans, with point-in-time restore available without manual intervention.
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Built-in monitoring
Cluster health, query performance, and resource utilization are tracked continuously, no external observability stack required.
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SQL Scheduler and table policies
Automates recurring tasks like data expiry, aggregation, and compaction directly within the platform, eliminating external pipelines.
Strengths and trade-offs
Strengths
- Production-grade CrateDB clusters are deployed in under a minute without any infrastructure provisioning or configuration files.
- Dedicated plans support up to 9 nodes, 144 vCPUs, and 495 GB RAM, with elastic scaling that rebalances the cluster automatically.
- Native vector search and full-text search are built into the SQL engine, eliminating the need for separate systems like Elasticsearch.
- Supports the PostgreSQL wire protocol, making it compatible with any Postgres-compatible tool and easing migration from PostgreSQL.
Trade-offs
- Operational simplicity reduces fine-grained control compared to ClickHouse's tunable columnar engine and merge tree configuration.
- Native vector search is limited for large-scale AI workloads that require dedicated vector databases with specialized indexing.
- Some users report that CrateDB requires more tuning for peak performance on specific query patterns compared to ClickHouse.
- Production-scale Dedicated plans start at $0.246/hour, which can accumulate significant cost for clusters with many nodes.
Pricing context
Three plans: a free tier for development, Shared plans for smaller workloads, and Dedicated plans starting at $0.246/hour with basic support and uptime SLAs. Custom configurations available for large production workloads. Pay by credit card, invoice, or through AWS, Azure, or GCP Marketplace.
Getting started with CrateDB Cloud
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Sign up for CrateDB Cloud
Go to the CrateDB Cloud website and create an account. Choose a free tier, Shared, or Dedicated plan. Verify your email and log in to the console.
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Deploy your first cluster
In the console, click Create Cluster. Select your cloud provider (AWS, Azure, or GCP) and region. Choose a plan and node size. Click Deploy; the cluster is ready in under a minute.
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Connect with your SQL client
From the cluster overview, copy the connection string. Open your PostgreSQL-compatible client (e.g., psql, DBeaver). Connect using the provided host, port, database name, and credentials.
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Load sample data and query
Run CREATE TABLE and INSERT statements to load sample time-series or JSON data. Execute SELECT queries with aggregations, full-text search, or geospatial functions to verify the engine works.
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Schedule automated tasks
Use the SQL Scheduler in the console to create recurring jobs, such as data expiry or aggregation. Define table policies for compaction and retention. Monitor execution in the built-in dashboard.
Frequently Asked Questions
What is CrateDB Cloud and what does it do?
CrateDB Cloud is a fully managed distributed database service that combines time-series, JSON, relational, vector, full-text, and geospatial data models into a single SQL-accessible engine. It runs natively on AWS, Azure, or GCP and deploys in under a minute.
How does CrateDB Cloud pricing work?
CrateDB Cloud offers three plans: a free tier for development, Shared plans for smaller workloads, and Dedicated plans starting at $0.246 per hour with basic support and uptime SLAs. Custom configurations are available for large production workloads, and you can pay by credit card or through cloud marketplaces.
How does CrateDB Cloud compare to ClickHouse?
CrateDB Cloud trades some raw analytical throughput on purely structured data for multi-model flexibility, including native vector search and dynamic schema. It automates sharding and rebalancing, while ClickHouse requires manual tuning of table engines and shard keys.
What are the key features of CrateDB Cloud?
Key features include fully managed operations, automatic sharding and rebalancing, zero-downtime upgrades, automated hourly backups with point-in-time restore, built-in monitoring, and a SQL Scheduler for automating data expiry and aggregation tasks.
What are the limitations of CrateDB Cloud?
CrateDB Cloud offers less fine-grained control than ClickHouse's tunable columnar engine. Its native vector search is limited for large-scale AI workloads. Some users report needing more tuning for peak performance on specific query patterns, and Dedicated plans can become costly for clusters with many nodes.
Is CrateDB Cloud compatible with PostgreSQL?
Yes, CrateDB Cloud supports the PostgreSQL wire protocol, making it compatible with existing Postgres tooling and easing migration from PostgreSQL. This allows teams to use familiar tools while gaining multi-model support and real-time analytics capabilities.
Alternatives
How CrateDB Cloud compares
Direct head-to-head against 2 competitors. Picked by 7wData.
CrateDB Cloud
- Pricing
- Three plans: a free tier for development, Shared plans for smaller workloads, and Dedicated plans starting at $0.246/hour with basic support and uptime SLAs. Custom configurations available for large production workloads. Pay by credit card, invoice, or through AWS, Azure, or GCP Marketplace.
- Target
- CrateDB Cloud is a fully managed, distributed database service that combines time-series, JSON, relational, vector, full-text, and geospatial data models into a single SQL-accessible engine.
- Strength
- Production-grade CrateDB clusters are deployed in under a minute without any infrastructure provisioning or configuration files.
- Watch for
- Operational simplicity reduces fine-grained control compared to ClickHouse's tunable columnar engine and merge tree configuration.
ClickHouse Cloud
- Pricing
- Pay-as-you-go from $0.10/hour; fixed plans from $47/month
- Target
- Real-time analytics on large volumes of structured data
- Deployment
- Managed cloud, self-hosted, hybrid
- Strength
- Columnar storage for sub-second SQL on billions of rows
- Watch for
- Requires careful schema tuning; complex JOIN performance
MongoDB Atlas
- Pricing
- Free tier; serverless from $0.10/hour; dedicated from $57/month
- Target
- Document-oriented workloads with flexible schemas
- Deployment
- Managed cloud, multi-cloud, on-premises
- Strength
- Native JSON document model and rich query language
- Watch for
- Cost escalation at scale; no native SQL support
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