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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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Tinybird
✓ verifiedFreemium
Managed ClickHouse platform giving developers hosted ingestion and query APIs to ship real-time analytics products fast.
104K visits/mo
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Jam
✓ verifiedFreemium
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
730K visits/mo2.9K saves
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Trunk
✓ verifiedFreemium
CI reliability platform that auto-quarantines flaky tests and runs an intelligent GitHub merge queue for engineering teams.
35K visits/mo
Pricing
Free: $0/mo (0.25 vCPUs, 1k requests/day, 10GB storage)
Developer: $49/mo (0.5 vCPUs, 25GB storage, 2 replicas)
No public pricing
Free: $0 (30 Jams/mo, 5 recording links)
Team: $14/creator per month billed yearly (unlimited Jams)
Free trial available
Free: $0/committer/month (up to 5 committers, 5M test spans/month)
Free trial available
Core features
- ✦Managed, hosted ClickHouse database
- ✦Sub-second SQL query APIs
- ✦Kafka and other data connectors
- ✦Safe, zero-downtime schema migrations
- ✦Git-based branching with zero-copy prod data
- ✦SOC 2 Type II enterprise security
- ✦Fully managed TiDB service
- ✦Easy deployment on AWS, Google Cloud, Azure, and Alibaba Cloud
- ✦Scalable and reliable MySQL-compatible database
- ✦Elastic scaling of storage, transactional, and analytical workloads
- ✦Robust security compliance (SOC 1/2/3, ISO 27001/27701, PCI DSS, GDPR, HIPAA)
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦Automatic flaky test detection and quarantining
- ✦AI-powered failure analysis and duplicate detection
- ✦Anti-flake protection in the merge queue
- ✦Batching up to 100 PRs with auto-bisection on failure
- ✦Parallel merge queues for non-overlapping changes
- ✦Integrated ticketing with Linear/Jira and Slack alerts
Use cases
- →Building real-time analytics dashboards
- →Powering in-app usage or event analytics
- →Streaming Kafka topics into query-ready tables
- →Letting AI coding agents build and deploy analytics
- →Building mission-critical applications requiring scalable and reliable databases
- →Managing and scaling transactional and analytical workloads
- →Deploying databases across multiple cloud providers and regions
- →Ensuring data security and compliance with industry standards
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Eliminating flaky test re-runs that slow down CI
- →Managing high-volume PR merges in a monorepo
- →Getting visibility into which tests impact the most pull requests
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