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Apache Flink vs. Striim

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Flink
Score 9.0 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
Striim
Score 8.3 out of 10
N/A
Striim is an enterprise-grade platform that offers continuous real-time data ingestion, high-speed in-flight stream processing, and sub-second delivery of data to cloud and on-premises endpoints.
$4,400
per month per 100 million Striim events
Pricing
Apache FlinkStriim
Editions & Modules
No answers on this topic
Striim Cloud Enterprise Platform
$4,400
per month per 100 million Striim events
Striim Platform
$20,000
per year per VCPU
Offerings
Pricing Offerings
Apache FlinkStriim
Free Trial
NoYes
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 FlinkStriim
Considered Both Products
Apache Flink
Verified User
Anonymous
Chose Apache Flink
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 …
Striim
Chose Striim
Faster, checkpointing better. CDC works well. The loading is faster. Easy upgrade and installation. Uses less resource.
Features
Apache FlinkStriim
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Flink
8.7
Ratings
8% above category average
Striim
-
Ratings
Real-Time Data Analysis10.00 Ratings00 Ratings
Data Ingestion from Multiple Data Sources7.00 Ratings00 Ratings
Low Latency10.00 Ratings00 Ratings
Data wrangling and preparation6.00 Ratings00 Ratings
Linear Scale-Out9.00 Ratings00 Ratings
Data Enrichment10.00 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Apache Flink
-
Ratings
Striim
10.0
Ratings
18% above category average
Connect to traditional data sources00 Ratings10.00 Ratings
Connecto to Big Data and NoSQL00 Ratings10.00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Apache Flink
-
Ratings
Striim
8.9
Ratings
9% above category average
Simple transformations00 Ratings10.00 Ratings
Complex transformations00 Ratings7.80 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Apache Flink
-
Ratings
Striim
8.5
Ratings
6% above category average
Data model creation00 Ratings8.40 Ratings
Metadata management00 Ratings8.40 Ratings
Business rules and workflow00 Ratings9.00 Ratings
Collaboration00 Ratings7.80 Ratings
Testing and debugging00 Ratings7.20 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Apache Flink
-
Ratings
Striim
9.5
Ratings
16% above category average
Integration with data quality tools00 Ratings9.00 Ratings
Integration with MDM tools00 Ratings10.00 Ratings
Best Alternatives
Apache FlinkStriim
Small Businesses
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10
Skyvia
Skyvia
Score 9.9 out of 10
Medium-sized Companies
Confluent
Confluent
Score 9.9 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 6.6 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache FlinkStriim
Likelihood to Recommend
9.0
(0 ratings)
8.8
(0 ratings)
User Testimonials
Apache FlinkStriim
Likelihood to Recommend
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
Read full review
Below samples are the well suited use cases; - Change data capture feature seamlessly works on popular RDMS. You can make enrichments on several data sources within the same Striim application. - You can install stand alone agents and start streaming log files to Striim servers. This is mainly useful for security operations or audit trail use cases.
Verified User
Anonymous
Read full review
Pros
  • 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
Read full review
  • GoldenGate Trail reader which iss faster than Oracle CDC. It does not used logminer, hence there is no load on source Oracle database.
  • Easy installation and upgrade in 5 minutes
  • Support is very good. Fast and user friendly.
RJ
Read full review
Cons
  • 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
Read full review
  • License a bit expensive
RJ
Read full review
Alternatives Considered
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
Read full review
Faster, checkpointing better. CDC works well. The loading is faster. Easy upgrade and installation. Uses less resource.
RJ
Read full review
Return on Investment
  • 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
Read full review
  • We got the license at a discount price
RJ
Read full review
ScreenShots