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Druid Review

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Very good

Revainrating 5 out of 5  
Rating 
4.8
IT Management, Columnar Databases

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Description of Druid

Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics solution for real-time data. It includes stream and batch ingestion, column-oriented storage, time-optimized partitioning, native OLAP and search indexing, SQL and REST support, flexible schemas; all with true horizontal scalability on a shared nothing, cloud native architecture that makes it easy to deploy, monitor and manage at scale. It is downloadable for free for unlimited use from druid.apache.org and also hosted in the cloud by Imply Data.

Reviews

Global ratings 3
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Type of review

I like how you can easily query your data without having to write any code. The UI could be easier to understand but overall this product has been great so far! There isn't much i dislike about this software yet. If there was anything i would say its that sometimes when querying certain metrics they don't show up correctly or are missing completely. This is not always their fault though as sometimes some of these types of problems are caused by our own data collection system which we haven't…

Pros
  • It's easy for anyone in my team who wants access too it, even those with no experience at all should know what buttons do something specific instead requiring them learn SQL queries etc just because one needs extra knowledge doesn’t mean everyone does.it also provides real time dashboards allowing us see trends within seconds rather than days if needed.
  • It allows me an insight into everything from performance information/health analytics
Cons
  • Almost never

Revainrating 5 out of 5

Easy ingestion / analysis for storing & visualizing big event streams

I like how you can easily add new columns or tables without having to worry about compatibility issues between versions of Druid. You have to be careful when adding new fields as they may not work well with older versions of Druid (e.g., if you're using Spark). The UI could definitely improve - there's no way to filter down rows after searching through them. Also, sometimes searches don't return results even though you know you should get some back. We've been able to solve our problems related

Pros
  • Data ingestion is easy.
  • Scales horizontally/vertically for any amountof nodes(one node = one datalake)
  • Can perform complex queries at scale fast enoughwithing single JVM instance
Cons
  • Some cons

Revainrating 4 out of 5

Great choice for BI platform with room for growth

Easy implementation of queries using sql like syntax along side custom built ones which has been very helpful when we have different teams building reports against same datastore without having them interfering or conflicting over their changes. As well its ability (or lack there off) to store large volumes efficiently while still being fast enough was one area. i found us missing out during initial prototyping phase but since then they reworked performance issues so should be fine going…

Pros
  • We were able implement some complicated SQL requests with ease as did joins / unions etc
  • user needs skills beyond just coding
Cons
  • It is hard to say