Dive into the power of utilizing SingleStore with Explo for your real-time embedded analytics use cases. Follow this step-by-step blog and see how easy it is to connect and use the products together for real-time insights.
Explo and SingleStore are two of the leading providers of embedded analytics and real-time data management, respectively. Together, these tools combine into a powerful engine for ingesting and displaying large amounts of data in real time — creating powerful analytics insights for end users. With SingleStore and Explo, the possibilities are endless for enabling real-time analytics experiences for customers. This blog dives into SingleStore and Explo, the combined benefits of the tools and why they are the best options in the market today.
What is the benefit of using SingleStore?
SingleStore is a data platform for real-time analytics and generative AI applications. SingleStore’s distributed SQL architecture enables high throughput transactional data, low latency analytics and context from real-time vector data. SingleStore can scale infinitely, has milliseconds of query latency, can handle millions of upserts per second and has 100x faster JSON analytics. SingleStore can handle hundreds of concurrent users running complex queries with single-digit millisecond query times, which scales wonderfully with built-in horizontal scalability.
SingleStore is also capable of being deployed in the cloud or on-premise, and is a zero-hassle setup experience. Compared to Oracle, SingleStore is over 4x cheaper and 10x faster.
SingleStore is the choice amongst real-time relational database management systems — made for speed, scale and simplicity.
What is the benefit of using Explo?
Explo is an embedded analytics provider focused on end-user customizability. Users leverage Explo’s low-code solution to build analytics experiences that range from static dashboards to self-service report builders. Teams can then take this experience they create and embed it in their web application for users to consume. Explo saves time building charts from scratch, writing SQL and optimizing analytics, enabling teams to focus on their core business.
With editable customer sections and Report Builder product lines, Explo is the best option for end-users to customize their own analytics experience. Additionally, these feature sets are ready for embedding out-of-the-box, enabling this highly bespoke and customizable experience without overwhelming founders, engineers, product managers or customer success managers who typically would need to set up these experiences.
Explo is also an easy-to-use tool, enabling teams to create complex analytics experiences with just a few point-and-click actions, all powered by a simple SQL interface.
Connecting SingleStore to Explo for embedded real-time analytics
To realize the power of these two tools together, we need to connect them. The process for connecting these experiences is incredibly fast and borderline seamless — the following is an easy, step-by-step guide to connect SingleStore and Explo.
Step 1. Install and set up SingleStore and Explo
Before integrating, you need to have both SingleStore and Explo installed and set up. To sign up for an account with SingleStore's cloud offering, go here. To sign up for an Explo account, go here.
Step 2. Get credentials from SingleStore
First, login to SingleStore and click on the three dots of your workspace, then click 'Connect Directly'. This will open up another page for us to begin the SingleStore connection process.
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Next, navigate to BI Tools and 'Other' to see your credentials for connecting SingleStore to Explo.
Finally, whitelist the Explo IP addresses in the Firewall tab to enable Explo to connect to the database without being blocked.
Step 3. Establish a connection from SingleStore to Explo
Once both platforms are set up, you can establish a connection from SingleStore to Explo. In the Explo dashboard, go to the 'Data' tab and choose 'Connect Datasource'. Choose 'SingleStore' as your database, fill in your SingleStore credentials and establish the connection. In just a few clicks, we are able to set up a read-only connection to our SingleStore database, enabling you to then make complex SQL queries against it without any coding!
Step 4. Create SingleStore dashboard
Once your data is imported you can start creating dashboards, the Explo experience for creating charts that can be embedded in your application. Navigate to the 'Dashboards' tab and click 'Create Dashboard'.
Step 5. Write SQL
In the dashboard, write SQL to access your data. In this case, we are grabbing real-time eCommerce data. We will do a simple Select * from our eCommerce dataset and limit the results to 100. Click 'Save and Run' to see a sample of your data.
Step 6. Create a chart
Visualize your data via a chart in Explo. Drag on a chart, select the dataset to create a visualization from,, defining the x- and y-axis for the chart. In this case, we are visualizing freight value over time as an eCommerce shipper. In Explo, we simply define the freight shipping date and aggregate that by month as the x-axis and, in the y-axis, we put the sum of the freight value. In a simple setup, we are able to get total freight value by month in a beautiful visualization!
Step 7. Embed in your application
Finally, we have a great visualization experience we want to share with the world. To do that, all we have to do is click a few buttons to get embed code for adding this experience to our application. In just 10 lines or fewer, we have a fully embedded, white labeled end-user embedded analytics experience to share!
What are some example use cases between Explo and SingleStore for embedded real-time analytics?
Explo and SingleStore are perfect for any real-time embedded analytics use case. If you’re building software in any of the following industries, there could be a strong use case for leveraging third-party tools for embedded analytics.
Manufacturing and industrial automation. Modern manufacturing requires real-time insights into the assembly line to ensure smooth operations. Real-time embedded analytics enables this information to get to the team fast, so problems — or soon-to-be problems — are quickly corrected.
Healthcare and medical devices. Healthcare outcomes often require immediate intervention from a trained professional. Real-time embedded analytics enable next-gen monitoring experiences to ensure good outcomes for patients.
Retail and eCommerce. Retail can be an extremely fast-paced environment, requiring down-to-the minute reordering and restocking. Real-time embedded analytics enables a retail purchasing and restocking team to be on top of inventory, ensuring customers get the goods and services they need on time, as modern consumers expect.
Telecommunications. Telecommunications can utilize real-time embedded analytics to see disruptions in network performance, making sure to make corrections to those interruptions to avoid cascading or prolonged issues.
Finance and banking. Financial transactions (especially in a digital-first world) have become near real time, making it harder than ever to detect problems and squash them before they grow out of control. Real-time embedded analytics enables finance teams to detect fraud in real time and intervene in situations that could pose problems for the underlying financial institution.
Energy and utilities. Energy grids require very precise management of load versus demand; a major imbalance can cause issues and blackouts for thousands of customers. Embedded analytics enables power grid overseers to see issues in real time, taking corrective action in case of energy or usage spikes/troughs.
Transportation and logistics. Transportation requires the coordination of dozens — or even hundreds of individuals — to complete a given delivery. As consumers demand more physical goods, transportation and logistics needs to be more on top of its fleet and route management. Real-time embedded analytics enables transportation to react to changes in real time, rerouting and managing fleets more efficiently.
Should I use Explo and SingleStore if I have an AI use case?
Absolutely! SingleStore offers one of the best AI databases in the market when it comes to easily searchable vector embeddings, enabling real-time AI functionalities. Additionally, Explo has built-in AI features to enable end-users to ask natural language questions and receive complex visualizations based on those requests. Combined, SingleStore and Explo are a next-level solution for real-time, generative AI solutions.
Embedded real-time analytics with Explo and SingleStore
Explo and SingleStore both tackle very different problems — but together combine into a singular solution to provide real-time embedded analytics. This is especially important in a digital-first world, with insights being streamlined in seconds as opposed to hours or days. It’s important to have a workflow that scales to meet these needs.
SingleStore is incredible for the data scalability aspect, just as Explo is a perfect solution for the end-user dashboarding. Explo and SingleStore are tools that are committed to the future of real-time analytics and together, will be able to create more real-time embedded analytics solutions to match the fast-paced nature of the data market today. Hopefully this piece helped to give more insights into what Explo and SingleStore can provide for customers!
