What’s new in Imply Polaris, our real-time analytics DBaaS – September 2023
Oct 12, 2023
Matt Morrissey
Every week, we add new features and capabilities to Imply Polaris. Throughout September, we’ve focused on enhancing your experience as you explore trials, navigate data integration, oversee data management, and create compelling visualizations.
New to Polaris? Here’s a quick rundown: Polaris begins with a Database-as-a-Service, powered by Apache Druid®, delivering all the benefits of a fully managed cloud service. What sets it apart are the built-in capabilities for data ingestion and visualization. In mere minutes, you can extract insights from your data without the hassle of infrastructure setup. You can utilize the same cloud database for end-to-end data management, benefiting from automatic tuning and continuous upgrades for peak performance at every stage.
So, what’s new in store for you?
1. Efficiency and Isolation: The Power of Multiple Projects
Introducing Multiple Projects in Imply Polaris – a feature designed for enhanced scalability and control. In Imply Polaris, a project serves as a fundamental unit, encompassing tables, data sources, files, jobs, visualizations, alerts, and reports. Notably, Polaris offers the unique capability of assigning distinct permissions to users for each project. This flexibility allows a user, who may have one role in one project, to easily take on a different role in another project.
Use Cases of Multiple Projects
Multiple projects in Imply Polaris bring a wealth of benefits and here’s why:
Environment Separation
Picture this scenario – you have a new data source, and you want to experiment with it without disrupting your existing setup. With multiple projects, you can now separate your work into distinct environments such as development, staging, and production. This means you can innovate and test new data sources and visualizations in the development project without affecting the stability of your staging or production projects.
Departmental or Customer Organization
If you operate in a multi-departmental or multi-client environment, you understand the need to keep data and resources isolated. Multiple projects allow you to efficiently structure Polaris based on distinct departments or customers. For example, each Polaris project can be tailored with its own specific set of permissions, configurations, and resources. This flexibility simplifies the process of addressing the diverse needs of your organization while ensuring customer data isolation.
Regional Flexibility
For organizations that span multiple geographic regions or data centers, the ability to create projects across regions is a tremendous asset. While we have long supported projects in multiple regions, you can now create multiple projects within the same secondary or tertiary region. This means you can establish projects for ‘North America,’ ‘Europe,’ or ‘Asia-Pacific,’ and within each of these regions, you can create and manage multiple projects. This allows for finer resource allocation and optimized services tailored to each region’s unique requirements, much like setting up distinct operational hubs within a region.
Unified Usage and Billing View
Imply Polaris also offers a unified view of usage and billing across all projects within your organization. This simplifies resource tracking and billing processes, ensuring transparent and efficient management of project-related costs
Imply Polaris API for Multiple Projects:
In addition to these features, the Imply Polaris API now seamlessly supports multiple projects, enhancing project management, organization, and resource allocation. Users can programmatically create, modify, or delete projects, streamlining project lifecycle management.
2. Streamline Data Workflows: Automatic Table Creation
We’re introducing a practical enhancement to Imply Polaris tailored to developers: Automatic Table Creation. This feature simplifies data ingestion by removing the need to manually create tables before starting an ingestion job. Polaris automatically defines the table’s name, schema mode, and type, simplifying data ingestion and streamlining the workflow.
Not only does Automatic Table Creation simplify data management, but it also reduces the risk of schema-related errors. It ensures that your tables are correctly configured, minimizing data ingestion failures. By eliminating manual table setup, you gain quicker access to data insights while avoiding any potential errors.
To enable this behavior through API, set createTableIfNotExists to true in the ingestion job spec.
3. Simplify Evaluation: Credit-Based Trials and Starter Project Size
We’re introducing two practical features in Imply Polaris to simplify your platform evaluation process: Credit-Based Trials and the Starter Project Size. These enhancements are aimed at helping developers explore Imply Polaris in a simple, cost-effective manner.
Credit-Based Trials for Cost-Effective Exploration
New users receive $500 in credits for a no-cost trial. Dive into Polaris without worrying about immediate costs. It’s a straightforward way to assess the platform without financial constraints.
Starter Project Size Optimized for Testing
This is designed for functional evaluation during trials or proof of concept. The Starter Project Size includes 25 GB of storage capacity, a minimum of 4 vCPUs, and 16 GB of RAM. This setup is perfect for product evaluation, enabling you to evaluate Polaris with your actual data and workloads.
Together, these features provide a 30-day evaluation period with full access to Polaris’s features and resources. You can start with the Starter Project size and leverage credits to easily switch between different projects. Explore Polaris cost-effectively, test it with real data, and make well-informed decisions about its suitability for your projects.
4. Flexible Data Visualization: Polaris integration with Grafana
While Imply Polaris comes with its own built-in visualization capabilities, we understand the value of seamlessly integrating Polaris with your existing business intelligence tools. This enables you to explore, query, and share your data with your tools of choice.
Polaris already provides the capability to visualize your data using popular tools like Tableau, Apache Superset, and Looker. Now, we’re excited to announce that Grafana is yet another available option for data visualization.
This integration with Grafana opens up new possibilities for leveraging your existing visualization solutions. For instance, if your organization uses Grafana for observability purposes, you can now extend its utility to visualize data for your analytics applications, all powered by Polaris. This means you can leverage your preferred visualization tool across a wider range of use cases, promoting efficiency and flexibility in your data analysis workflows.
Ready to get started? Sign up for a free 30-day trial of Imply Polaris—no credit card is required! As always, we’re here to help—if you want to learn more or simply have questions, set up a demo with an Imply expert.
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