Apache Druid vs. CrateDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Druid
Score 10.0 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
CrateDB
Score 0.0 out of 10
N/A
CrateDB is an open-source, distributed SQL database for relational and time-series data, from Crate.io headquartered in San Francisco. A solution for machine data, the vendor states CrateDB is purpose-built for the need to scale volume, variety and velocity of data while running aggregated complex real-time queries, anywhere and without driving up costs.
$53
per month
Pricing
Apache DruidCrateDB
Editions & Modules
No answers on this topic
Shared S2
$53
per month
Shared S4
$103
per month
Shared S6
$153
per month
Dedicated CR1
$187.25
per month
Shared S12
$303
per month
Dedicated CR2
$362.45
per month
Dedicated CR3
$712.85
per month
Dedicated CR4
$ 1,413.65
per month
Open Source
Free for Self-Hosting
Custom
Custom
Custom
Offerings
Pricing Offerings
DruidCrateDB
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
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User Ratings
Apache DruidCrateDB
Likelihood to Recommend
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Apache DruidCrateDB
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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Pros
  • Rapid ingest
  • Limiting ingest to only the relevant fields/columns
  • Easy ingest spec creation
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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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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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ScreenShots