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What is Hitachi Streaming Data Platform?

The Hitachi Streaming Data Platform (SDP) is specifically designed for the real-time processing of large volumes of time-series data as it is generated. By leveraging in-memory and incremental computation methods, SDP facilitates swift analyses that avoid the usual lags associated with traditional data processing approaches. Users can define summary analysis scenarios using Continuous Query Language (CQL), which has a syntax similar to SQL, thereby allowing flexible and programmable data analysis without the need for custom-built applications. The platform's architecture comprises various elements such as development servers, data-transfer servers, data-analysis servers, and dashboard servers, which collectively form a scalable and efficient ecosystem for data processing. Moreover, SDP’s modular architecture supports numerous data input and output formats, including text files and HTTP packets, and integrates effortlessly with visualization tools like RTView for real-time performance tracking. This thoughtful design guarantees that users can proficiently manage and analyze their data streams as they happen, ultimately empowering them with actionable insights. As a result, organizations can respond more quickly to changing data conditions, significantly enhancing their operational agility.

What is Apache Flink?

Apache Flink is a robust framework and distributed processing engine designed for executing stateful computations on both continuous and finite data streams. It has been specifically developed to function effortlessly across different cluster settings, providing computations with remarkable in-memory speed and the ability to scale. Data in various forms is produced as a steady stream of events, which includes credit card transactions, sensor readings, machine logs, and user activities on websites or mobile applications. The strengths of Apache Flink become especially apparent in its ability to manage both unbounded and bounded data sets effectively. Its sophisticated handling of time and state enables Flink's runtime to cater to a diverse array of applications that work with unbounded streams. When it comes to bounded streams, Flink utilizes tailored algorithms and data structures that are optimized for fixed-size data collections, ensuring exceptional performance. In addition, Flink's capability to integrate with various resource managers adds to its adaptability across different computing platforms. As a result, Flink proves to be an invaluable resource for developers in pursuit of efficient and dependable solutions for stream processing, making it a go-to choice in the data engineering landscape.

Media

Media

Integrations Supported

Alibaba Log Service
Amazon Managed Service for Apache Flink
Apache Doris
Apache Zeppelin
Arroyo
Deep.BI
Foundational
Gable
GlassFlow
Hadoop
Hue
IBM Event Automation
Netdata
Redpanda Agentic Data Plane
Scalytics Connect
StarTree
VeloDB
Ververica
lakeFS

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Not specified

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Hitachi

Company Location

Japan

Company Website

www.hitachi.com

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

flink.apache.org

Categories and Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Categories and Features

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