As more and more businesses move to the cloud, it has become imperative for them to find an optimal data storage solution for this modern computing architecture
One of the best choices for businesses is the Snowflake data warehouse.
We will look at the best tools for Snowflake usage monitoring because these very same businesses will need them to get the most out of their cloud data storage solution.
Here is our list of the best tools for Snowflake usage monitoring:
- Datadog A cloud-observability platform that also monitors Snowflake usage and data security; it reports on current and historical usage information and makes
- Tableau A popular tool for data visualization offers interactive and exportable dashboards; it is easy to use and handles large amounts of data with no latency.
- New Relic Another popular tool that integrates well with Snowflake; it spots expensive queries, users with too many jobs running, and poorly performing queries for easy cost analysis.
- Toucan Toco An easy-to-use platform for data analysis dashboards; it allows for collaborative work on resource planning, security auditing, or any other custom jobs required by users.
- Looker A web-based data visualization and BI platform that can translate user-generated designs into SQL queries; it makes it easy to share dashboards with all stakeholders or embed them in custom apps.
- DataSunrise A database performance monitoring tool that is easy to install and use; it can be implemented on-premises or in the cloud and integrates well enough to start monitoring and reporting on database traffic quickly.
- Aginity An SQL analysis tool that saves users’ queries and jobs for later retrieval; it helps with the efficient use of Snowflake and ensures optimal utilization of resources when running queries and analytics.
What is Snowflake?
Snowflake is often described as “the data warehouse built for the cloud” because it uses and runs on a new SQL database engine with a unique architecture that was designed for the cloud.
While this Data Warehouse as a Service (DWaaS) is primarily built on top of the Amazon Web Services (AWS) cloud infrastructure, it also uses Google Cloud and Microsoft Azure services. As a true SaaS offering, it is a popular choice for enterprises migrating their workloads to the cloud, aiming for a low-maintenance but highly scalable data warehouse.
Although Snowflake has all the data for usage, cost, performance, and security readily available in its SNOWFLAKE database, it isn’t user-friendly. That is why we need to use one of the best tools for Snowflake usage monitoring that we will see in detail.
What is Snowflake used for?
The primary use of Snowflake is as a cloud data platform that allows users to store, manage, analyze, and share high volumes of structured and semi-structured data with ease.
Snowflake’s Data Cloud brings down data silos and any barriers between a business’ data sources to serve as a single source for all its workloads.
What are some features to look for in a good Snowflake usage monitor?
Let’s have a look at some features that make for good Snowflake monitoring tools:
- Automation A good usage monitoring tool should perform its tasks without manual intervention or having to write any code. It is expected to offer competent performance right out of the box.
- Scalability A cloud warehouse solution like Snowflake is highly scalable to accommodate large surges of data; the monitoring tool should also be able to scale easily if it is of any use at peak times.
- Real-time monitoring A management tool should be able to monitor around the clock and report on performance at will, without any latency.
- Data transformation It should modify data that needs to be processed before it is exported or displayed.
- Intuitive reporting The whole purpose of a monitoring tool is to show all the relevant information clearly and understandably using dashboards and interactive graphics that can also be embedded in other applications.
- Price A software solution’s investment in a software solution always depends on its return on investment (ROI); therefore, a good Snowflake usage monitoring tool should always be worth the price.
With these points in mind, we have selected the tools to be included in this list.
The Best Tools for Snowflake Usage Monitoring
Let’s move on and have a more detailed look at the best tools for Snowflake monitoring:
1. Datadog
Datadog is a cloud-observability platform for the modern networking environment. It offers a collection of modules for data analysis, server monitoring, and database administration.
Key Features:
- It allows for the optimal usage of storage spaces, improvement of performance, and cost control of Snowflake instances.
- It monitors the warehouse’s performance and can compute credit consumption while detecting misconfigurations and security threats.
- It has out-of-the-box dashboards that can track the amount of data stored in the warehouse; it can, for example, pinpoint which users are incurring the highest Snowflake storage costs.
- In case of overuse, Datadog can proactively adjust warehouse sizes or clusters before capacities are exceeded; it has forecasting alerts driven by machine learning to keep administrators informed.
- Meanwhile, the administrators are made aware of any deviations from historical patterns or fluctuations in storage usage with the help of anomaly detection monitors.
- They can break down information silos between various teams – including developers, security, and operation teams – while improving collaboration across the organization using a single, unified, and intuitive platform.
- The tool monitors key query performance metrics in real-time to help avoid queuing queries caused by warehouse overloads; it catches any issues and optimizes performances.
- Threat detection capabilities allow for identifying security misconfigurations, login attempts, and detailed observability of data from the entire local and remote stack.
It also has an integration that gives insight into Snowflake data warehouses.
Try Datadog for FREE for 14 days.
2. Tableau
Tableau is perhaps the most popular tool for visualizing data. It has highly intuitive and interactive dashboards while providing in-depth information that can be further drilled down into.
Key Features:
- Tableau is well-known for its user-friendliness, which allows it to cater to users with all backgrounds – from novice to expert – and its ability to present data in highly interactive dashboards backed by an extensive library of charts.
- It is an excellent tool for Snowflake usage monitoring, too – it handles millions of data rows with ease, can work with various data sources for integrated analysis, and brings it all under interactive dashboards for the user.
- Tableau has designed several dashboards in partnership with Snowflake to help stakeholders seamlessly monitor the usage of this particular technology investment.
- It has Account Usage views that provide information at the user level with user-based filters that allow managers to drill down and see information on their teams’ details; they can set up data-driven alerts for real-time notifications that daily or monthly consumption thresholds can trigger.
- Administrators can identify times when utilization is low and optimize their Warehouse sizing accordingly; the Compute Cost Overview dashboard can show credit burn for budget allocation and cutting unnecessary spending.
What’s more, it has a superior capability of bridging data from various warehouses, including Snowflake and bringing it all together to create a comprehensive image.
Try Tableau for FREE.
3. New Relic
New Relic is another major player in the platform and digital assets monitoring tools field. It integrates with Snowflake to monitor query performance, logins, and potential security incidents.
Key Features:
- New Relic detects warehouse performance issues to help with their quick resolution; it can also see potential security issues like failed login attempts, for example, to reduce the chances of unauthorized access.
- It helps optimize storage costs by spotting expensive queries, users running too many questions, or warehouses that are too expensive with little to no return on investments.
- It monitors and sends out alerts on custom Snowflake data and queries; it funnels monitoring results to security reports for further handling.
- Cost analysis via user data to identify poor query performances and help perform root-cause analysis on them.
- It sends alerts when query performances fall below set threshold limits; it can be configured to alert on Snowflake disk spillages. When query queues become too long, it even points out specific inefficient and poorly written queries among them.
- It collects a wide range of performance-related data and enables users to ingest any data stored in Snowflake to get complete visibility; it also makes it easy to export custom data from Snowflake for external consumption and analysis.
It can be used to track and optimize warehouse or cloud credit costs and capture any data stored in Snowflake for real-time alerting and reporting.
Try New Relic for FREE.
4. Toucan Toco
Toucan Toco offers a platform for data analysis dashboards that technical and non-technical decision-makers can use.
Key Features:
- Toucan Toco can audit Snowflake usage and security threats like unusual login attempts.
- It offers other summarized and action-driven warehouse monitoring insights into key Snowflake data warehousing metrics.
- It brings all Snowflake technical and non–technical stakeholders on board; they can share the insights, invite other colleagues to apps, send PDF reports, and make comments.
- Users can use the tool’s presentation mode for meetings and present live data instead of relying on static tables from popular tools like MS Excel or MS PowerPoint.
- It is easy and safe to connect to Snowflake monitoring data; the tool allows users to set up a trusted OAuth Snowflake integration and credentials to access their data.
- It makes it easy to troubleshoot Snowflake by identifying query optimization opportunities; users can simply drill down into high-level analysis for granular insights for information like query frequency, duration, rows returned, and the number of errors encountered.
- It has an adaptive design for complete customization and the ability to embed charts into other applications or websites; it can be deployed to other devices quickly without extra work, installation, or post-deployment care needed.
The users can collaborate on the decision-making process while communicating their actionable insights via built-in no-code frameworks and third-party applications like Teams and Slack.
Try Toucan Toco FREE for 15 days.
5. Looker
Looker (now part of Google Cloud) is a web-based data visualization and BI platform for creating business reports and real-time dashboards. Its users can connect, analyze, and visualize data across multi-cloud environments.
Key Features:
- Looker connects with Snowflake, Redshift, BigQuery, and over 50 supported SQL dialects; users can run analysis on multiple databases, avoid database lock-in, and monitor multi-cloud data environments.
- Because Snowflake’s own advanced SQL dialect is rich in features, users can leverage all the power and flexibility of the warehouse directly from Looker.
- Users can quickly analyze structured and semi-structured data; they can store their data in Snowflake and then adapt Looker to fit the data and maintain granular control access from Looker.
- It is fast – administrators can use the tool to empower everyone in the organization with access to the data they need. They can then perform analysis and reporting on Warehouse usage and performance regardless of data sizes being queried or the number of users accessing data.
- Looker offers stakeholders unified access to the answers they need to drive successful outcomes; they can create custom apps that can deliver data experiences that are as unique as their businesses.
A unique feature with this tool is that Looker can transform Graphical User Interface (GUI) based user input into SQL queries and then send it directly to the database in live mode. Users create LookLML projects that convert the designs into executable SQL queries.
Try Looker – request a FREE demo.
6. DataSunrise
DataSunrise is a database performance monitoring tool for Snowflake databases. It can give administrators insights into DBMS functioning and performance while helping to understand the root causes of issues that may lead to malfunctioning and underperformance of Snowflake warehouses.
Key Features:
- It is easy to install, configure, and manage in the cloud and on-premises; it integrates well into existing architectures with a non-intrusive deployment, and everything remains unchanged.
- DataSunrise simplifies Snowflake’s operation assessment; it helps with the immediate identification of bottlenecks and other operational delays in the database.
- It should be noted that this tool’s primary function is monitoring the databases’ security rather than keeping an eye on usage and cost analysis – although it does a great job of that too, albeit with a bit of manual intervention required.
- Administrators can examine running scripts to detect the ones causing problems; they can even evaluate the queries executed in transactions and eliminate vulnerabilities that tamper with the normal performance of a Snowflake database.
- They can also monitor database traffic – and queries – across the whole database integration; the tool’s Activity Monitoring feature allows for detecting SQL injections and suspicious access requests.
- The tool further shows the query owners’ entire session data, like their IP addresses and hostnames.
- DataSunrise can generate throughput reports that show traffic flow between clients and databases, database error reporting, authorization attempt loggings, and session data recordings.
Try DataSunrise for FREE.
7. Aginity
Aginity is an SQL analysis tool used to connect and monitor Snowflake queries. The tool questions queries, relationships, and snippets for reuse in SQL statements. Users can find their previous commands in query histories and catalogs.
Key Features:
- Aginity comes with Snowflake starter catalogs on Github that must be imported for instant access to hundreds of helpful SQL utilities, queries, and snippets.
- Snowflake provides general availability of External Tables – snapshots or extracts of data that users need to work on – and Aginity supports this feature; users can use these External Tables to run ad-hoc analytics via queries without having to resort back to the main storage.
- Users can define, document, and save standard analytics in personal catalogs; they can describe code with rich titles and descriptions to help them remember what they do.
- They can create data models and schemas to analyze data across database platforms and build flexible, commonly used data-cleansing SQL code.
- Reusing the saved code for common SQL logic saves time during analysis and reporting and helps train the tool’s machine-learning models.
- Aginity offers the flexibility of storing the SQL code to generate periodic reports by inserting and merging rows into report tables; users can also combine tasks with table streams for continuous ELT workflows and follow-up jobs on changed data.
- The tool has a Database Explorer for scheduling tasks to run SQL statements independently – including making calls to stored procedures.
It allows analysts to maintain data warehouses, design data models and schema designs, and connect the system with various databases like Snowflake, Amazon AWS, IBM Cloud, and Microsoft Azure.
Try Aginity for FREE for 30 days.
Make a move to the data warehouse of the cloud
If you are making plans to move into cloud data storage, we highly recommend using Snowflake. However, while you’re at it, we also recommend that you choose one of the Snowflake usage monitoring tools to go with it. After all, an important investment needs a reliable monitoring tool.
Let us know what you think. Leave us a comment below.
