Apache Flink and Starburst Enterprise are competing in the real-time data processing and analytics category. Apache Flink has an edge in stream processing, whereas Starburst Enterprise excels in data integration and analytics flexibility.
Features: Apache Flink's notable features include stateful computation, strong event processing capabilities, and support for complex event-driven applications. Starburst Enterprise offers comprehensive data exploration, integration with diverse data platforms, and a high-performance distributed query engine.
Ease of Deployment and Customer Service: Apache Flink provides flexible deployment options across cloud and on-premises environments, focusing on containerized deployment strategies, with community-based support channels. Starburst Enterprise offers a user-friendly setup with excellent customer support, ensuring smooth deployments and comprehensive technical assistance.
Pricing and ROI: Apache Flink typically offers lower setup costs, providing strong ROI for streaming applications but might need significant customization for particular use cases. Starburst Enterprise generally involves higher initial costs, but its robust analytics capabilities and resource management tools lead to substantial long-term ROI, appealing to enterprises with strategic data initiatives.
Apache Flink is an open-source batch and stream data processing engine. It can be used for batch, micro-batch, and real-time processing. Flink is a programming model that combines the benefits of batch processing and streaming analytics by providing a unified programming interface for both data sources, allowing users to write programs that seamlessly switch between the two modes. It can also be used for interactive queries.
Flink can be used as an alternative to MapReduce for executing iterative algorithms on large datasets in parallel. It was developed specifically for large to extremely large data sets that require complex iterative algorithms.
Flink is a fast and reliable framework developed in Java, Scala, and Python. It runs on the cluster that consists of data nodes and managers. It has a rich set of features that can be used out of the box in order to build sophisticated applications.
Flink has a robust API and is ready to be used with Hadoop, Cassandra, Hive, Impala, Kafka, MySQL/MariaDB, Neo4j, as well as any other NoSQL database.
Apache Flink Features
Apache Flink Benefits
Reviews from Real Users
Apache Flink stands out among its competitors for a number of reasons. Two major ones are its low latency and its user-friendly interface. PeerSpot users take note of the advantages of these features in their reviews:
The head of data and analytics at a computer software company notes, “The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis.”
Ertugrul A., manager at a computer software company, writes, “It's usable and affordable. It is user-friendly and the reporting is good.”
Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.
By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.
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