Tiger Cloud: Performance, Scale, Enterprise, Free
Self-hosted products
MST
The following table compares the features available in Tiger Cloud and self-hosted TimescaleDB Community Edition.
| Feature | Tiger Cloud on AWS | Tiger Cloud on Azure | TimescaleDB |
|---|---|---|---|
| Best-in-сlass Postgres performance | |||
| Automatic partitioning via hypertables for efficient indexes and faster ingest | ✓ | ✓ | ✓ |
| Continuous aggregates | ✓ | ✓ | ✓ |
| Time/partition-oriented constraint exclusion for faster queries | ✓ | ✓ | ✓ |
Skip scans, ordered appends, custom optimizations for faster LIMIT and DISTINCT queries | ✓ | ✓ | ✓ |
| Columnar storage for accelerated scans | ✓ | ✓ | ✓ |
| Vectorized query execution (SIMD) | ✓ | ✓ | ✓ |
| Specialized vector indexes for AI applications | ✓ | ✓ | ✓ |
| Source Postgres connector | ✓ | ✓ | Manual |
| Source S3 connector | ✓ | ✗ | ✗ |
| Source Apache Kafka connector | ✓ | ✗ | ✗ |
| Tiger Lake destination connector from Tiger Cloud to Iceberg-backed S3 Tables | ✓ | ✗ | ✗ |
| In-Console CSV, Parquet, and text file imports | ✓ | ✗ | ✗ |
| Flexible analysis with full SQL | |||
| Complete Postgres ecosystem including all Postgres features, connectors, and third-party drivers | ✓ | ✓ | ✓ |
| Cross-table JOINs for time-series and events tables with relational tables | ✓ | ✓ | ✓ |
| Rich timestamp and timezone support | ✓ | ✓ | ✓ |
| Flexible time-bucketing for time-oriented analysis | ✓ | ✓ | ✓ |
| Advanced hyperfunctions including interpolation, approximation, and visualization functions | ✓ | ✓ | ✓ |
| Geospatial and vector data types | ✓ | ✓ | ✓ |
| Automated data management | |||
| Native compression (up to 98% storage savings) | ✓ | ✓ | ✓ |
| Columnar storage format with fast scans | ✓ | ✓ | ✓ |
| Data retention policies | ✓ | ✓ | ✓ |
| Data tiering with automated policies | ✓ | ✗ | ✗ |
| Data reordering for efficient disk scans | ✓ | ✓ | ✓ |
| Data downsampling for efficient historical analysis | ✓ | ✓ | ✓ |
| Background job scheduler and user-defined jobs | ✓ | ✓ | ✓ |
| Enterprise scalability | |||
| Disaggregated compute and storage | ✓ | ✓ | Manual |
| Dynamic compute resizing | ✓ | ✓ | ✗ |
| Dynamic disk storage with usage-based pricing | ✓ | ✓ | ✗ |
| Dynamic I/O provisioning for high-read/ high-write performance | ✓ | ✓ | Manual |
| Low-cost storage with infinite capacity on S3 | ✓ | ✗ | ✗ |
| Transparent queries across high-performance and low-cost tiers | ✓ | ✗ | ✗ |
| Read replicas with load balancing for seamless read scaling | ✓ | ✓ | Manual |
| Connection pooling for connection scaling | ✓ | ✓ | Manual |
| Automated resource-aware parameter tuning | ✓ | ✓ | ✗ |
| Terraform for infrastructure-as-code control | ✓ | ✓ | ✗ |
| High availability and reliability | |||
| Multi-AZ deployments for high availability | ✓ | ✓ | Manual |
| Continuous incremental backup and automated restore | ✓ | ✓ | Manual |
| Cross-region backup | ✓ | 🔜 | ✗ |
| Point-in-time recovery and branching | ✓ | ✓ | Manual |
| Regular database and disk snapshots to enable fast restore | ✓ | ✓ | ✗ |
| Rapid recovery for all services by fast database restart and remote disk remount | ✓ | ✓ | ✗ |
| Memory guard protections to avoid database out-of-memory crashes | ✓ | ✓ | ✗ |
| Decoupled control/data planes for greater resilience | ✓ | ✓ | ✗ |
| Commercial SLAs | ✓ | ✓ | ✗ |
| Automated upgrades and software patching | |||
| Automated upgrades during maintenance windows | ✓ | ✓ | ✗ |
| Phased, zero-downtime TimescaleDB and Postgres minor upgrades | ✓ | ✓ | ✗ |
| Postgres major version upgrades with forking workflow and disk snapshots to minimize downtime | ✓ | ✓ | ✗ |
| HA-replica-aware coordinated upgrades | ✓ | ✓ | ✗ |
| Fleet-wide version and stability monitoring with staged roll-out/roll-back upgrades | ✓ | ✓ | ✗ |
| Security and compliance | |||
| SOC 2 Type 2, GDPR, HIPAA certified compliance | ✓ | ✓ | ✗ |
| Data encryption at rest (both disk and backup) | ✓ | ✓ | Manual |
| Data encryption in transit | ✓ | ✓ | Manual |
| Database SSL with fully verifiable certificate chains | ✓ | ✓ | ✗ |
| Control plane role-based access control | ✓ | ✓ | ✗ |
| Database role-based access control | ✓ | ✓ | ✓ |
| Multi-factor authentication | ✓ | ✓ | ✗ |
| Corporate SSO and SAML | ✓ | ✓ | ✗ |
| VPC peering | ✓ | ✗ | ✗ |
| AWS Transit Gateway | ✓ | ✗ | ✗ |
| Layered database "privilege escalation" protections | ✓ | ✓ | ✗ |
| Secure SDLC practices and vulnerability scanning, third-party pen testing | ✓ | ✓ | ✗ |
| Deep observability | |||
| Operational database visibility to understand performance, uncover regressions, optimize performance | ✓ | ✓ | ✗ |
| Automated query analysis and statistics | ✓ | ✓ | ✗ |
| Per-query drill-downs into execution times, row results, plans, memory buffer management, cache performance | ✓ | ✓ | ✗ |
| In-Console metric visualization and system logs | ✓ | ✓ | ✗ |
| Exporters to AWS CloudWatch, Prometheus, Datadog | ✓ | ✗ | ✗ |
| Connection monitoring | ✓ | ✓ | Manual |
| Connection management | ✓ | ✓ | Manual |
| Production-grade support and operations | |||
| 24/7 follow-the-sun support with global support team across APAC, EMEA, and Americas | ✓ | ✓ | Contact sales |
| Production support (severity 1) | ✓ | ✓ | Contact sales |
| Architectural reviews, data modeling, and query optimization and assistance, feature testing, and migration support | ✓ | ✓ | Contact sales |
| 24/7 operational monitoring and control | ✓ | ✓ | Contact sales |
| 98%+ customer satisfaction (CSAT scores) | ✓ | ✓ | Contact sales |
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