Apache Druid vs. TimescaleDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Druid
Score 8.8 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
TimescaleDB
Score 0.0 out of 10
N/A
Timescale headquartered in New York provides their eponymous time series database TimescaleDB in community and enterprise editions.N/A
Pricing
Apache DruidTimescaleDB
Editions & Modules
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Offerings
Pricing Offerings
DruidTimescaleDB
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
Best Alternatives
Apache DruidTimescaleDB
Small Businesses
InfluxDB
InfluxDB
Score 8.5 out of 10
InfluxDB
InfluxDB
Score 8.5 out of 10
Medium-sized Companies

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Enterprises

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All AlternativesView all alternativesView all alternatives
User Ratings
Apache DruidTimescaleDB
Likelihood to Recommend
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
Apache DruidTimescaleDB
Likelihood to Recommend
Apache
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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Timescale
No answers on this topic
Pros
Apache
  • Rapid ingest
  • Limiting ingest to only the relevant fields/columns
  • Easy ingest spec creation
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Timescale
No answers on this topic
Cons
Apache
  • Security configuration is problematic
  • Cluster management could have more features
  • Troubleshooting incomplete tasks/jobs is a chore
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Timescale
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Return on Investment
Apache
  • 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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Timescale
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ScreenShots