Apache Druid vs. MonetDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Druid
Score 9.0 out of 10
N/A
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture.N/A
MonetDB
Score 7.0 out of 10
N/A
MonetDB is an open source column-oriented relational database management system issued and supported by the Dutch MonetDB development team.N/A
Pricing
Apache DruidMonetDB
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DruidMonetDB
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache DruidMonetDB
Best Alternatives
Apache DruidMonetDB
Small Businesses
InfluxDB
InfluxDB
Score 8.8 out of 10
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Medium-sized Companies

No answers on this topic

InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Enterprises

No answers on this topic

SAP IQ
SAP IQ
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache DruidMonetDB
Likelihood to Recommend
9.0
(0 ratings)
7.0
(0 ratings)
User Testimonials
Apache DruidMonetDB
Likelihood to Recommend
It is extremely well suited to rapid ingest of data from large data sources, due to the fact that you can restrict what is ingested by column/field, so that you only pull in the data you actually want or need.
As stated earlier, the open source version could use better cluster management tools, and troubleshooting tools for failing jobs/tasks.
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I think for what we use it for, mainly scheduling, forecast and to compare against payroll, it works well. I think there are some other things that could be added to it to use, like more expansive ways to use the forecasting tool and an easier way to pull previous data from prior years. This would help making the forecast for scheduling in the future.
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Pros
  • Rapid ingest
  • Limiting ingest to only the relevant fields/columns
  • Easy ingest spec creation
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  • It is easy to use.
  • You are able to input lots of data and it understands and populates information.
  • Able to change settings on the fly to use with your needs.
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Cons
  • Security configuration is problematic
  • Cluster management could have more features
  • Troubleshooting incomplete tasks/jobs is a chore
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  • This is an open source software so there are obvious drawbacks, the biggest of which is a lack of documentation.
  • MonetDB does not seem to be well known outside of the academic environment so there is less information when you are searching for answers of any type.
  • I'd like to see more use cases and/or best practices so that commercial companies like ours can optimally use all of its highly performant features.
  • The code is written in C/C++ and this can be negative if you are a mainly java-shop and need UDF - User Defined Function.
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Alternatives Considered
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There is a plethora of choices when it comes to NoSQL and columnar based databases. We use not one but sometimes 2 or 3 of them to carry out a specific purpose. We chose MonetDB because our engineering team enjoys working with open source software and appreciates its simplicity although becoming familiar with it did take time. I would not deploy MonetDB to production but it's a great backup option.
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Return on Investment
  • Integration with S3 storage has saved about 35% on our storage, over HDFS
  • The rapid ingest has saved user's time in the query aspects of their applications.
  • The ability to ingest from a variety of data sources has made overall user application queries much simpler
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  • If you are familiar with a general database concept and played with open source products before then MonetDB will give you immediate return in terms of productivity since developers can quickly develop and verify their test cases involving back-end database with a large sample data set.
  • There is a stiff learning curve due to lack of documentation and sparse information available on the internet.
  • Overall experience has been positive since MonetDB gives you another option when it comes to building out a data warehouse.
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