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The 5-Minute Interview: Sifting Through Science

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The 5-Minute Interview: Sifting Through Science

Among the many uses of graph databases is the ability to quickly and efficiently sift through the always-increasing amount of scientific data.

· Database Zone
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Learn how to create flexible schemas in a relational database using SQL for JSON.

“We think it’s good to use the right tool for the right problem — and graph databases are the right tool if you are focusing on relationships,” said Antonio Molins, Vice President of Data Science at Miroculus.

Choosing the right database for the right use case is a critical decision that, when made correctly, allows your data to reach its highest potential.

In this week’s 5-Minute Interview (conducted at GraphConnect San Francisco), we discuss how this molecular diagnostics company uses Neo4j to sort through newly-available scientific data.


Talk to us about how you use Neo4j at Miroculus.

Antonio Molins: Miroculus is a molecular diagnostics company, and we are currently focusing on recently-discovered microRNAs. In order to make sense of all the newly available microRNA information, we are storing this high volume of data in a searchable graph databaseNeo4j is a great fit for that.

What made you choose to work with Neo4j?

Molins: We really like the platform as well as the UI, even though we ended up building our own open-access UI in the end. We think it both performs and scales well, which is why we went with Neo4j.

Knowing everything you know now, if you could go back in time and start over again with Neo4j, is there anything you would do differently?

Molins: When we first started using Neo4j we were only querying online and storing things locally instead of in a database. If we could start over again, we would have integrated Neo4j earlier in the process.

Is there anything else you’d like to add?

Molins: We think it’s good to use the right tool for the right problem, and graph databases are the right tool if you are focusing on relationships. I’d recommend it for anybody with a similar use case.

Create flexible schemas using dynamic columns for semi-structured data. Learn how.

Topics:
neo4j ,graph databases ,data science ,database

Published at DZone with permission of Bryce Merkl Sasaki, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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