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Instantly understand Amazon Redshift performance, dependencies, and bottlenecks

Amazon Redshift is incredibly powerful. But scaling your workloads takes careful planning. We take the guesswork out of that, so you can spend more time being creative with your data.

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See across your cluster, data apps and users

Making sense of thousands of varying data points takes a lot of time and resources. That’s why we give you the capability to see your data journey from source to analysis, right from your dashboard. So you can measure performance and discover insights you can act on. Our daily emails keep you in the loop on your cluster. With Streams, you can send metrics to Amazon CloudWatch and set alerts on your most critical workloads.

Fix slow dashboards and run faster queries

Even with the power of a large Redshift cluster, queries can still get slow. Throughput and Memory Analytics help you discover the right Workload Management (WLM) configuration. In the context of cluster usage, you can start to understand where the data is stuck, so you can get it flowing again. Need to know what sort key and distribution style to pick? Our Table Analytics give you the power to do just that.

Plan ahead and grow with your data

With business growth comes data growth. More data leads to more analysis. When joining data sets, analysts and algorithms create new, derived data. Which can be much larger than the original source data. Our Storage Analytics give you the power to predict your future storage needs. Track your schemas, tables and the workflows that make them grow. With our custom vacuum scripts, you can keep your cluster lean and save time.

Way easier than trying to figure things out with scripts


Everything you need to be successful in your job is the missing piece of your data infrastructure. Our intelligent monitoring for Amazon Redshift helps you identify and fix your bottlenecks. No more jumping between tools and scripts. Our curated UIs give you a single, comprehensive view of your entire Redshift stack — ETL jobs, scheduled workflows and BI tools. Every change, every second, in full context.

Discover & Search

Ask questions about your queries and loads. Which users write the most expensive queries? What’s the average query latency? How much time do queries wait in the queue? Which transformations are too slow or failing?

Load & Query analytics

Get times-series reports for your data transfers and queries. With details on transfer rates, counts, queue and execution times.

Advanced search

Powerful full-text search capabilities across all queries, data transfers, and user activity. Narrow down your search with filters and complex rules.

Top loads & queries

Identify the top tables by size per schema and database. See all tables which need vacuuming to reclaim and reuse space.

Query details

Sort all tables by disk utilization and data growth rates. Spot tables with accelerating growth that could fill up your cluster.

Workload Management Analytics

Our Workload Management Analytics help you discover the right WLM configuration for your Amazon Redshift cluster. In context with cluster usage, you start understanding which apps are responsible for usage peaks and keep data from flowing. Maximize data throughput by fine-tuning memory and concurrency slots in your query queues.

WLM details

Intuitive auto-discovery of WLM queues, user groups, memory and concurrency settings. See all your cluster settings in a single view.

Concurrency analysis

Identify concurrency bottlenecks that slow down your queries. See with time-series data when queries get stuck waiting in the queue.

Query group summary

Isolate key queries with automatic grouping. Track their performance over time to identify opportunities to increase query speeds.

Storage & Table Analytics

Many data teams ingest event data continuously and run their ETL processes within Amazon Redshift. Some processing can run outside with Amazon Redshift Spectrum, Amazon Athena or Spark. But Amazon Redshift remains critical for data access for team members. Knowing what's driving data growth, down to the single table, is key to fine-tune your cluster size. Our dashboards help you remove the guessing and show you in detail what happens when you make changes.

Disk utilization

Analyze disk use by node, database, schema and table. Predict storage needs with data growth rates for each individual table.

Schema & Table sizes

Identify the top tables by size per schema and database. See all tables which need vacuuming to reclaim and reuse space.

Table sorting

Sort all tables by disk utilization and data growth rates. Spot tables with accelerating growth that could fill up your cluster.

Vacuum scripts

Save time by downloading and running custom vacuum scripts. Reduce the storage footprint of your data.

Make your data team more productive
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