Tiger Cloud (from the creators of TimescaleDB) is a fully-managed TimescaleDB solution, hosted on AWS and designed for real-time analytics on high-ingest, high-read time series workloads. Start today with $1,000 in free trial credits; trial credits expire in 30 days.
IoT and Industrial Monitoring: Companies ingesting sensor data from thousands to millions of devices (20M+ measurements per day)
Financial Services: Trading platforms, Crypto and digital wallets, exchanges requiring analytics, time-weighted averages and real-time aggregations
Energy (Oil & Gas) and Utilities: Organizations analyzing production data, consumption patterns, and equipment performance
Key Tiger Cloud features:
Built on 100% unforked Postgres, Tiger Cloud is designed to support:
Automatic partitioning (Hypertables): Turn any Postgres table into a hypertable that automatically partitions data by time (and optionally space/dimension) for fast ingest even as datasets grow.
Hybrid row/columnar storage (Hypercore): Handle both transactional and analytical workloads efficiently.
Native compression: Reduce storage costs and speed up analytics by compressing historical data up to 95%, while keeping it fully queryable through the same SQL interface.
Precompute common analytical queries and refresh them incrementally (Continuous aggregates): Real-time dashboards stay responsive without batch jobs or materialized view maintenance.
Independent storage and compute scaling: Scale compute resources and storage capacity separately based on actual workload needs and pay only for what you use.
Automatic data tiering to object storage: Historical data automatically moves to low-cost object storage while remaining queryable. Reduce storage costs without losing accessibility.
Read replicas for workload isolation: Run analytical queries on dedicated replicas and avoid resource contention with production writes to maintain transactional performance.
Native Hybrid Search: Combine high-performance HNSW vector search (pgvectorscale) with BM25 keyword ranking (pg_textsearch), without the complexity of managing a separate vector database or Elasticsearch cluster.
Native integration with your data lakehouse (Tiger Lake): Automatically synchronize hypertables and relational tables running in Tiger Cloud services with Apache Iceberg tables running in Amazon S3.
Deep integration with your AWS ecosystem: Native ingestion paths for Kafka/Amazon MSK, RDS for PostgreSQL and Aurora PostgreSQL, along with S3 and Postgres connectors stream operational data directly into Tiger Cloud-provides secure connectivity, streaming and batch ingest, observability, analytics, AI and billing.
Enterprise readiness: Production-grade uptime SLAs, regional data isolation, compliance certifications, backups, High Availability, and 24/7 support reduces operational risk.
Highlights
Start today with $1,000 in free trial credits; trial credits expire in 30 days.
100% unforked Postgres: Full SQL compatibility for rapid adoption and integration.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
You buy this listing through a single Total Commitment Value dimension. This is a usage-based, pay-as-you-go setup, so you draw down against your committed amount as you consume resources. You pay for two things: compute, metered hourly, and storage, metered by average GB used per hour. Both scale up or down automatically with your workload, and you can change compute at any time. Certain add-ons, such as high-availability replicas, tiered storage, and production support, can add to your usage charges. Billing runs monthly in arrears based on actual consumption.
Top-of-mind questions for buyers
What does the hourly compute charge map to, and how is it counted?
Compute is metered hourly against the CPU and memory configured for each database service. If a service runs part of the month at one CPU size and part at another, you pay each rate for the hours actually run at that size. You can scale compute up or down anytime.
How do compute and storage charges combine to produce my monthly bill?
Both charges apply at once on one invoice. Compute reflects hourly CPU and memory usage. Storage reflects average GB used per hour, growing and shrinking with your data. Compute-heavy workloads see compute dominate; large historical datasets with low query rates see storage weigh more. Add-ons like replicas and tiered storage add separate line items.
How does adding high-availability or read replicas change my cost?
HA and read replicas are charged at the same rate as your primary service, based on the compute and primary storage each replica consumes. Data moved to the low-cost object storage tier is shared across all replicas, so replicas reading tiered data do not add to your bill.
Request a private offer to receive a custom quote.
How can we make this page better?
Tell us how we can improve this page, or report an issue with this product.
Give us feedbackReport a problem with this product or seller
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA).
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
TigerData provides cloud support services for Tiger Cloud customers in two tiers:
Basic Support: Automatically included with all subscriptions, providing essential assistance for your cloud operations.
Production Support: Designed for mission-critical environments, offering 24x7 coverage and priority response to ensure your applications run smoothly at all times.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Tiger Cloud (from the creators of TimescaleDB) is a fully-managed TimescaleDB solution, hosted on AWS and designed for real-time analytics on high-ingest, high-read time series workloads. Start today with a 30-day free trial.
TigerGraph Cloud is the industry's first and only distributed, native graph database-as-a-service - built for innovators who would rather focus on building breakthrough applications than managing infrastructure. Designed to power both real-time analytics and transactional workloads, TigerGraph Cloud helps businesses harness the power of connected data at scale.
TigerGraph Savanna is purpose-built for real-time analytics, advanced AI/ML applications, and large-scale data exploration. Trusted by Fortune 500 companies and AI innovators alike, Savanna powers mission-critical use cases including fraud detection, customer intelligence, supply chain optimization, cybersecurity, and AI-driven recommendations.
It is easy to access, analyze and visualize data. I really liked how it processes large datasets and provides clear, actionable insights to look for. The dashboard for pc version is also user friendly and customizable, and helps to stay updated for the changing trends in the market. It has definitely improved the speed and accuracy of decision-making in my work. Also, i preferred it's former name (timescale) but new name is also good.
What do you dislike about the product?
there are times when the interface feels a bit heavy, especially when dealing with large volumes of data. The mobile version could also be more optimized for smoother usage on the go with better UI.
What problems is the product solving and how is that benefiting you?
Currently, I am catering a client where i have to deal and analyze good size data where tigerdata comes into the picture.
Computer & Network Security
My Experience using tiger data
Reviewed on Sep 26, 2025
Review provided by G2
What do you like best about the product?
I like the clean and intuitive UI the most. It’s easy to navigate, and I appreciate the ability to pause services whenever needed. The availability of connectors, especially for Amazon S3 and Kafka, makes integration smooth and very useful.
What do you dislike about the product?
The pricing feels a bit high and could be more flexible, especially for smaller projects or startups.
What problems is the product solving and how is that benefiting you?
TigerData solves the usual trade-offs between real-time and analytical workloads: I get fast queries on fresh and historical data both, without needing to build and maintain complex pipelines. Its compression and tiered storage help keep costs down even as data volume grows. Also, the native integrations (lakehouse / S3) reduce overhead, making it easier to focus on insights rather than infrastructure.
Computer Software
Efficient and powerful database platform for scalable analytics
Reviewed on Sep 26, 2025
Review provided by G2
What do you like best about the product?
TigerData stands out for its extremely fast setup, reliable ingestion speeds, and intuitive cloud interface, making it easy to start and scale even complex analytical workloads. Its full PostgreSQL compatibility—plus handy vector database tools—enables seamless migrations and flexible querying without the need to learn new languages or disrupt existing workflows. Active community support through Discord and Slack, plus robust documentation, mean help is always available for developers and admins. Features like continuous aggregation, compression, and automatic partitioning allow teams to optimize performance and save on cloud costs, while its metrics dashboard provides clear insights into database health and usage.
What do you dislike about the product?
Although TigerData is highly performant, the UI can become slow to load when managing many tables, which impacts workflow efficiency for larger projects. Some users note the absence of advanced visualizers for vector data—features seen in competing products—which can limit analytic visualization capabilities. On rare occasions, initial self-hosted deployments may require extra troubleshooting, but most issues are quickly addressed by updates or community help. Additionally, TigerData’s licensing and query costs can be higher compared to certain open-source or basic database offerings, so budgeting is important when scaling up.
What problems is the product solving and how is that benefiting you?
TigerData enables reliable and high-speed storage and analysis for massive time series data, solving scaling bottlenecks and ingestion speed limitations experienced with traditional databases. It helps the team efficiently run real-time analytics, minimizes downtime, and saves on cloud costs thanks to automated compression and partitioning features. This has improved decision-making speed and operational reliability for data-driven products.
Dalius K.
Efficient easy to use platform
Reviewed on Sep 24, 2025
Review provided by G2
What do you like best about the product?
The platform provides various easy-to-use tools for analytics, making analytics simplier
What do you dislike about the product?
Need some time to learn features, have slow customer support.
What problems is the product solving and how is that benefiting you?
TigerData allows us to efficiently store and analyze large volumes of time-series and relational data. It reduces query times, simplifies data management, and provides actionable insights, improving decision-making and operational efficiency
Financial Services
Great out of the box solution for any PostgreSQL user
Reviewed on Jan 20, 2025
Review provided by G2
What do you like best about the product?
Easy to start, easy to maintain, easy to scale
What do you dislike about the product?
Recent pricing model change is not ideal
What problems is the product solving and how is that benefiting you?
Allows to store and query large about of financial time series data