<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=752538731515435&amp;ev=PageView&amp;noscript=1">

What Types of Data Can MarkLogic Search?

Google makes it look so easy.

Type in an addition problem, Google gives you a calculator.

Type in a city name followed by the word "weather" and Google returns a forecast.

Type in one city name to another city name, and Google returns flight information and a map.

There are also video clips, scans of book pages, and even the occasional tongue-in-cheek response (for example, search on the word askew).

You may not be in the business of maintaining weather forecasts or travel routes, but you do have data. Have you ever wondered if you'd ever be able to search across your internal data as easily as you use Google to search across the public internet?



Our tool of choice for building out internal data storage and search solutions is MarkLogic.

No, it's not "Google in a Box".

It's different.

Possibly better.

From the What is Marklogic page:

MarkLogic is an operational and transactional Enterprise NoSQL database that combines a transactional document repository with search indexing and an application server. MarkLogic applies a full-text index to the documents stored within its repository.


So - make a big database. Store data of all types in it. Store pointers to other data that you can't store directly. Then index it all for searching.

What types of data?

  • MS Office documents
  • Text delimited data
  • Relational databases
  • Geospatial data
  • Social media content
  • Financial trading data
  • Images
  • Video

We don’t need to know what the data looks like, we don’t need to go through a lengthy planning exercise before loading, there’s no need for scoping or data forecasting. Give us some data and in five to 10 days we’ll show you it searchable in our database. We had a trading data store application that brought together 20 databases live in 5 months.Adrian Carr, Vice President, Worldwide Commercial Sales at MarkLogic



But what's that all mean in real-world applications?

We went through the MarkLogic Solution Sheets and pulled out a few examples:

Law Enforcement

MarkLogic can access, extract, store and search across data provided by dashboard cameras, bodycams, closed circuit televisions (CCTV), automated number plate recognition (ANPR) systems, and other digital formats.


MarkLogic powers an app for a high-profile comedy television show. The app allows rabid fans to search across episodes based on scenes, guest stars, characters, etc and build themselves a customized playlist.


Major healthcare providers use MarkLogic to store and search across a wide range of data including:

  • Patient Generated data including health and treatment history, symptoms, and remote devices
  • Research data including medical journals, R&D, and life sciences
  • Clinical data including test lab results, discharge plans, and prescriptions
  • Population level data including demographics, census, and disease registries
  • Social medial data including Facebook, LinkedIn, Twitter, and blogs
  • Regulatory data including quality measures, adverse events, compliance and legal
  • Claims data including treatment codes and billing information


MarkLogic allowed a leading health care company to pull together over 200 sources of employee data and feed that to over 50 systems. All of this was coordinated in less than a year.

Got Data?

How much of your day is spent looking up data from different sources and aggregating it for another system? If the answer to that is "a lot", give us a shout. Let's see if a MarkLogic solution will eliminate some of that busy data work.

Maybe then you'll have time for Google Pac Man or Smarty Pins.

Elijah Bernstein-Cooper

About Author Elijah Bernstein-Cooper

Elijah Bernstein-Cooper is a former solutions consultant with Omni. He developed applications with MarkLogic. Prior to Omni, Elijah received his masters in astrophysics at the University of Wisconsin-Madison where he expanded his repertoire in data science. Elijah’s background in astrophysical data science complemented with NoSQL development allows him to provide fresh solutions for businesses’ challenges in data governance and analysis.


Omni’s blog is intended for informational purposes only. Any views or opinions expressed on this site belong to the authors, and do not represent those held by people or organizations with which Omni is affiliated, unless explicitly stated.

Although we try to the best of our ability to make sure the content of this blog is original, accurate and up-to-date, we make no claims of complete accuracy or completeness of the information on this site/s to which we link. Omni is not liable for any unintended errors or omissions, or for any losses, injuries, or damages from the display or use of this information. We encourage readers to conduct additional research before making decisions based on the information in this blog.