Apache Druid vs. Rockset

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
Rockset
Score 9.0 out of 10
N/A
Rockset is a serverless search and analytics engine that does fast SQL on NoSQL data from Kafka, DynamoDB, S3 and more. According to the vendor, it delivers millisecond-latency SQL over TBs of raw data, without any ETL. Rockset integrates with the user's database, data stream or data lake to continuously ingest new data without requiring a schema, while providing full SQL support for filtering, aggregations and joining streaming data with other data sets. Rockset powers data-driven applications…N/A
Pricing
Apache DruidRockset
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DruidRockset
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
User Ratings
Apache DruidRockset
Likelihood to Recommend
9.0
(0 ratings)
9.0
(0 ratings)
User Testimonials
Apache DruidRockset
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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1. Usage based billing - helpful in creating query lambdas and workflow around them. 2. Fast data refresh and scheduled running of queries is required. 3. Wherever real-time data is in play in terms of visibility.
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Pros
  • Rapid ingest
  • Limiting ingest to only the relevant fields/columns
  • Easy ingest spec creation
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  • Fast ingest and real-time indexing
  • Complex SQL queries run really fast
  • Lower cost in terms of deployment.
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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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  • User interface
  • AI in queries, auto-generated queries
  • Graphing tools
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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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  • Didn't need to invest in an external billing software.
  • Major customer feature ask was fulfilled - realtime usage overview
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