I've had several conversations lately where, at some point, I get the question "which vendors provide data product capabilities?"  It only took me hearing this question 5 or 6 times before I thought that perhaps I should create a list of embedded analytic providers.

My hope is that this will provide a good starting point for product leaders trying to select a vendor for their analytic application. 

Note: this isn't a list of recommended vendors or platforms, it's just... a list. If I've left out a vendor that you feel should be included, please let me know.

The Embedded Analytic/Data Product Vendor List

Birst (www.birst.com)

Birst is a powerful platform that offers it all, from data extraction to visualization to management. It has robust data management tools that allow teams to combine and control data from almost any sources. Birst was recently acquired by Infor, an enterprise software vendor.

Chartio (www.chartio.com)

No experience with this vendor but they offer embedded analytics capabilities.

GoodData (www.gooddata.com)

GoodData was a subject of our “Vendors You Should Know” review for August 2017. They offer fully-managed cloud-based analytics with a great support team to assist. Key differentiator here is the “Insights Platform” that uses machine learning to deliver automated insights alongside visualizations.

Exago (www.exagoinc.com)

No experience with this vendor but they offer embedded analytics capabilities.

Izenda (www.izenda.com)

Izenda is a platform purpose-built for data products. Unlike with some other analytic platforms, the focus is completely on data products. As a result, they’ve got the functionality that product leaders require, such as multiple embedding technologies, full white-labeling, built-in utilization analytics, and a complete management ecosystem. Look for a “Vendors You Should Know” write up shortly.

JuiceBox (www.juiceanalytics.com)

Juice is unique because rather than a “do it yourself” platform, they build data products for you. As a result, you get data products that are tightly integrated with your core product and look gorgeous. These folks live and breathe data products so they’re very likely to understand exactly how to make you successful.

Keen IO (www.keen.io)

No experience with this vendor but they offer embedded analytics capabilities.

LogiAnalytics (www.logianalytics.com)

Logi has been a pioneer in the embedded analytic space with good reason. The platform offering is highly customizable and addresses most, if not all, of the key needs of product owners. The product line has been revamped in recent years and is worth reviewing.

Looker (www.looker.com)

Looker was a subject of our “Vendors You Should Know” review for August 2017. By using modern technology and acting on your data in place, Looker can get data products up and running rapidly. They’ve got an excellent management ecosystem that allows teams to deploy (or rollback) functionality with ease. As a bonus, the Looker technology makes it extremely easy to create tiers (like basic, plus, or pro) for your users.

Microsoft PowerBI (powerbi.microsoft.com)

Unsurprisingly, PowerBI has made a huge impact in the embedded analytic space. Since it’s launch, the MS team has been adding functionality at a breakneck pace. My big concerns with this one are focus (vs other parts of a large product portfolio) and an evolving pricing model.

Microstrategy (www.microstrategy.com)

No personal experience on this vendor but MicroStrategy has been offering embedded analytics capabilities as long as anyone in the space. Worth checking out.

Mode Analytics (www.modeanalytics.com)

Mode Analytics offers a unique combination of power to create embedded analytic data products that work exactly like you want with the ease of use required by business users. It's a blend of features that you normally wouldn't find in a single platform. As a result, it can serve the needs of the most power-hungry data teams and product owners wanting to craft a curated experience for end-users.

Pentaho (www.pentaho.com)

Pentaho, now part of Hitachi, falls more into the “toolkit for building analytics” space. An excellent option for teams that want to build highly-customized data products without building completely from scratch, Pentaho may require more resources both for deployment and management than other solutions.

Qlik (www.qlik.com)

Qlik has been a major player in the analytic space for many years now and they offer embedded analytics as well as enterprise capabilities. Although I’ve seen large Qlik deployments of enterprise analytics, I can’t speak to their embedded capabilities.

Sisense (www.sisense.com)

Sisense, one of the up-and-comers in the embedded analytics space, provides some interesting capabilities for product leaders. They claim rapid deployment with complete whitelabling and the ability to scale to massive data and customer sets. Additionally, Sisense emphasizes data governance and security—essentials for data products.

SlamData (www.slamdata.com)

SlamData is unique in that it focuses on analytics for NoSQL databases. Unlike some solutions, this isn't just a mapping of one or two levels of your semi-structured data. Rather, it accesses all of your NoSQL data, no mapping or modeling required. The result is a robust, fast to implement, and easy to maintain platform for your data product.

Tableau (www.tableau.com)

Tableau is possibly the best known platform in the analytics space, but most people think of them as a desktop analysis tool. In fact, Tableau has offered embedded analytic capabilities for several years now. I don’t feel that their management ecosystems is quite as robust as some other solutions, but the visualizations are stunning.

YellowFin (www.yellowfinbi.com)

No experience with this vendor but they offer embedded analytics capabilities.

Zoomdata (www.zoomdata.com)

Zoomdata excels in handling large volumes of streaming data. Rather than moving the data to an analytic-ready storage location, Zoomdata connects to the data where it resides and provides analytics that “sharpen” as more data flows in. It’s a slick system and they’ve been emphasizing embedded analytics lately, but the robustness of the management ecosystem essential for data products is unknown to me.