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Apache Flink vs. Rockset

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Flink
Score 9.2 out of 10
N/A
Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. And FlinkCEP is the Complex Event Processing (CEP) library implemented on top of Flink. Users can detect event patterns in streams of events.N/A
Rockset
Score 8.9 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 FlinkRockset
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache FlinkRockset
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 FlinkRockset
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Apache FlinkRockset
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Flink
8.7
1 Ratings
7% above category average
Rockset
-
Ratings
Real-Time Data Analysis10.01 Ratings00 Ratings
Data Ingestion from Multiple Data Sources7.01 Ratings00 Ratings
Low Latency10.01 Ratings00 Ratings
Data wrangling and preparation6.01 Ratings00 Ratings
Linear Scale-Out9.01 Ratings00 Ratings
Data Enrichment10.01 Ratings00 Ratings
Best Alternatives
Apache FlinkRockset
Small Businesses
IBM Streams
IBM Streams
Score 9.0 out of 10
Algolia
Algolia
Score 8.9 out of 10
Medium-sized Companies
Confluent
Confluent
Score 7.4 out of 10
Guru
Guru
Score 9.0 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 8.1 out of 10
Guru
Guru
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache FlinkRockset
Likelihood to Recommend
9.0
(1 ratings)
9.0
(1 ratings)
User Testimonials
Apache FlinkRockset
Likelihood to Recommend
Apache
In well-suited scenarios, I would recommend using Apache Flink when you need to perform real-time analytics on streaming data, such as monitoring user activities, analyzing IoT device data, or processing financial transactions in real-time. It is also a good choice in scenarios where fault tolerance and consistency are crucial. I would not recommend it for simple batch processing pipelines or for teams that aren't experienced, as it might be overkill, and the steep learning curve may not justify the investment.
Verified User
Anonymous
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Rockset
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.
Verified User
Anonymous
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Pros
Apache
  • Low latency Stream Processing, enabling real-time analytics
  • Scalability, due its great parallel capabilities
  • Stateful Processing, providing several built-in fault tolerance systems
  • Flexibility, supporting both batch and stream processing
Verified User
Anonymous
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Rockset
  • Fast ingest and real-time indexing
  • Complex SQL queries run really fast
  • Lower cost in terms of deployment.
Verified User
Anonymous
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Cons
Apache
  • Python/SQL API, since both are relatively new, still misses a few features in comparison with the Java/Scala option
  • Steep Learning Curve, it's documentation could be improved to something more user-friendly, and it could also discuss more theoretical concepts than just coding
  • Community smaller than other frameworks
Verified User
Anonymous
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Rockset
  • User interface
  • AI in queries, auto-generated queries
  • Graphing tools
Verified User
Anonymous
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Alternatives Considered
Apache
Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and fault tolerance, Apache Flink takes the lead. However, Spark has a larger community and a decidedly lower learning curve.
Verified User
Anonymous
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Rockset
No answers on this topic
Return on Investment
Apache
  • Allowed for real-time data recovery, adding significant value to the busines
  • Enabled us to create new internal tools that we couldn't find in the market, becoming a strategic asset for the business
  • Enhanced the overall technical capability of the team
Verified User
Anonymous
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Rockset
  • Didn't need to invest in an external billing software.
  • Major customer feature ask was fulfilled - realtime usage overview
Verified User
Anonymous
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ScreenShots