Today, data is the new currency. Embedded analytics tools are the mint that turns raw numbers into valuable coins. This is the backbone of decision-making within multi-tenant applications.
It’s the difference between sailing blind and charting a course with precision. It’s ensuring that every decision is informed. Every action is strategic. Every opportunity is seized.
However, embedded analytics software is different than traditional analytics software. The scalability and multi-tenant data security needs often leave software engineering teams building more than they should.
So how do the various software providers for embedded analytics stack up? Let’s look…
What is Embedded Analytics Software?
Embedded analytics software empowers SaaS companies to offer customizable and self-service analytics directly within SaaS applications.
It enables SaaS companies to offer more than one-size-fits-all static reporting. Customers want their reports to be unique to their use case. They want data exploration on their terms.
It fuels competitive differentiation. This holds true no matter what industry you’re in.
Embedded analytics platforms however are not all the same. Most focus on how many colors a bar chart can handle, but the reality is that it starts with data. We put together a guide on the critical features to consider when evaluating embedded analytics vendors.
Companies understand that without a scalable, performant, multi-tenant data layer, the charting library almost doesn’t matter. BI companies that offer embedded analytics as a feature almost always struggle to make their customers successful.
Multi-tenant analytics software is harder than most believe. It requires extra layers of application logic to enforce tenant and user data security before anyone explores data.
Check out our deep dive on why multi-tenant analytics is harder than most understand.
The Best Embedded Analytics Tools for 2024
Qrvey
The leader in embedded analytics. Qrvey focuses exclusively on giving software development teams a turkey multi-tenant analytics solution. This focus enables Qrvey to understand the use cases of SaaS companies on a deeper level. Their goal is to empower software development teams to build less software.
Why Qrvey?
Qrvey takes a different approach. Qrvey is the only solution that includes a native data lake for enterprise scale, starting with a focus on data. This also includes a unified data pipeline that can connect to any data source, regardless of data type. This immediately enhances data readiness.
Qrvey then simplifies connecting into a multi-tenant SaaS platform with a seamless integration. Using a native semantic layer, integrating into the SaaS security model is fast by mapping permissions on the fly. A native suite of APIs opens use cases beyond traditional analytics such as data as a service.
Qrvey’s embedded analytics pricing includes unlimited users, dashboards, and environment deployments.
How Do Embedded Analytics Tools Compare for Multi-Tenant Analytics?
Most solution providers think embedded analytics is only about the charts. However, embedding within multi-tenant SaaS environments requires more than internal analytics. When choosing an embedded analytics tool, let’s look at areas like:
- How complete are they for embedding within a multi-tenant SaaS application?
- How cost-effective are they to scale concurrent queries?
- How well do they support personal analytics experiences?
Let’s compare common embedded business intelligence software solutions:
Yellowfin BI
Yellowfin BI is an Australian company. It is a business analytics platform that helps organizations use data for operational reporting. Core features include automating data analysis, interactive dashboards, and storytelling. Yellowfin primarily focuses on internal analytics.
How does Yellowfin compare against the best embedded analytics tool?
Pros
- Good support for chart-level customization
- Good for custom data stories analytics capabilities
- Automated data insights (available as an add-on)
Cons
- Direct connection to databases only. Up to you to scale data query performance.
- Emphasizes iFrame embedding on a separate subdomain, not within the SaaS application itself.
- Server-based hosting relies on server clustering to scale.
Yellowfin Embedded Pricing
They offer choices, but no prices on their website:
- Revenue share model
- Server cores
- “Aligned Utility Model: Price Per Unit”
Read our in-depth comparison here.
Sisense
Sisense is an Israeli company. Its business analytics software is for companies that want to turn data into actionable insights. Sisense helps users use their data, analyze it, and visualize it to make business decisions. Its primary use case is internal analytics.
How does Sisense stack up against the best embedded analytics platform?
Pros
- Good support for developer SDK for dashboards
- Offers a range of UI customizations
Cons
- Expensive server-based deployment. The minimum requirements to run both the application and ElastiCube require large, expensive servers.
- Difficult to integrate into a multi-tenant security model or use with real-time data
- ElastiCube is relational data only so ETL jobs need to happen with third-party products prior to ingestion.
Sisense Embedded Pricing
- Not published. Historically, they have charged for user licenses and individual server licenses.
Read our in-depth comparison here.
Sigma
Sigma is a cloud analytics platform. It uses a spreadsheet-style interface to give internal users access to analyze data from their cloud data warehouse.
How does Sigma compare against the best embedded analytics solution?
Pros
- Familiar to Excel
- Good UI customization features
- Good support for Snowflake data warehouse
Cons
- Relies on iFrames for embedding dashboards
- No data management. Leaves scaling up data warehouses to you.
- Pushes Snowflake, which is known to be expensive for high-concurrency analytics queries. A common feature of embedded analytics within SaaS applications.
Sigma Embedded Pricing
- $30k Platform fee + $1,000 Annual User Fee (to create dashboards), very limited free viewer-only licenses (as of 2023)
Luzmo
Luzmo (formerly Cumul.io) is a company from Belgium that focuses on embedded analytics. They offer a dashboard display and dashboard-building software for embedded use cases.
How does Luzmo stack up against the best embedded analytics software?
Pros
- Can start quickly to test it
- Has an embedded dashboard builder
Cons
- Pricing packages become expensive fast for larger SaaS companies
- No data management, extra processes need resources to prepare data for analytics
- Limited multi-tenant user security features
Luzmo Embedded Pricing
- Base package = $12k per year for 1 dashboard creator, 100 viewers, no white-labeling
- Elite package = $37k per year for 30 dashboard creators, 1000 viewers
Reveal BI
Reveal BI (owned by Infragistics) is a BI solution with a focus on embedded analytics. Reveal BI is a self-hosted solution.
How does Reveal BI stack up against the best embedded analytics software?
Pros
- Has an embedded SDK
- Can customize the look of the data visualizations
Cons
- No data management. Handling multiple queries at once is a different task
- Loads dashboards with iFrames
Reveal BI Pricing
- Not published on their website
Essential Features of the Best Embedded Analytics Tools
Embeddability
A strong embedded analytics solution should easily add analytical content for customers to see in applications, portals, or websites. It provides a modern data experience by putting reports, dashboards, and other analytics tools all in one place.
White Labeling
When embedding analytics, consider white labeling analytics to ensure a seamless integration. Users expect to stay within your application, and third-party analytics products can negatively impact the user experience.
Scalability for Concurrency
As the adoption of embedded analytics grows, your application must handle growing demand. Look for a platform that can efficiently analyze large volumes of data while maintaining security and scalability. Without scalable queries, you will quickly alienate users.
Granular Data Security & Access Controls
Administrators need to control who can see what data in detail. In systems with multiple users, it’s important to link user permissions to data permissions. Inheriting access from the parent SaaS application is the ideal method.
Deployability to SaaS Platforms
How easy is it to map user permissions to data security? Do you have to recreate users or can you pass in parameters? If you can map user security with JWT tokens like Qrvey, the integration will be far easier to maintain.
Also, confirm you can deploy to lower development environments. Any software engineering team will want to replicate production in lower environments.
Easy Data Integration
Pre-built data warehouse connectors and user-friendly APIs are essential for achieving fast time-to-market.
End-User Ease of Use
Embedded analytics should help all types of business users. That means even those without technical skills should be able to make and use dashboards and reports. Choose platforms that let users easily create detailed charts and reports by dragging and dropping elements.
No-Code Automation Workflows
Workflow automation makes data actionable. Look for no-code automation workflows that let users automate tasks and actions based on changing conditions. This makes it easy to create data-focused applications without needing technical skills.
In the end…
In summary, legacy solutions often fall short for embedded analytics use cases in multi-tenant environments. Qrvey addresses this gap by providing a full-stack solution that combines embedded visualization and self-service analytics tools. Qrvey also uses a scalable data lake to improve analytics for developers and end-users.
Watch a demo now to see for yourself.
Brian is the Head of Product Marketing at Qrvey, the leading provider of embedded analytics software for B2B SaaS companies. With over a decade of experience in the software industry, Brian has a deep understanding of the challenges and opportunities faced by product managers and developers when it comes to delivering data-driven experiences in SaaS applications. Brian shares his insights and expertise on topics related to embedded analytics, data visualization, and the role of analytics in product development.
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