About
Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes.
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About
Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.
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About
Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale.
Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries.
Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases.
Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements.
Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools.
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About
Wing Python IDE was designed from the ground up for Python, to bring you a more productive development experience. Type less and let Wing worry about the details. Get immediate feedback by writing your Python code interactively in the live runtime. Easily navigate code and documentation. Avoid common errors and find problems early with assistance from Wing's deep Python code analysis. Keep code clean with smart refactoring and code quality inspection. Debug any Python code. Inspect debug data and try out bug fixes interactively without restarting your app. Work locally or on a remote host, VM, or container. Wingware's 21 years of Python IDE experience bring you a more Pythonic development environment. Wing was designed from the ground up for Python, written in Python, and is extensible with Python. So you can be more productive.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Individuals in search of a tool to transform, filter, aggregate, and join data streams
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Audience
Companies and professionals seeking a solution to manage their streaming and batch data processing operations
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Audience
Organizations interested in a powerful real-time data warehouse
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Audience
Python developers seeking a tool to build applications
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationArroyo
United States
www.arroyo.dev/
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Company InformationSpring
spring.io/projects/spring-cloud-dataflow
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Company InformationVeloDB
Founded: 2023
Singapore
www.velodb.io
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Company InformationWingware
Founded: 1999
United States
wingware.com
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Categories |
Categories |
Categories |
Categories |
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Application Development Features
Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development
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Integrations
AWS Fargate
Apache Parquet
Apache Spark
Apache Tomcat
C
Django
Docker
Mercurial
MySQL
P4
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Integrations
AWS Fargate
Apache Parquet
Apache Spark
Apache Tomcat
C
Django
Docker
Mercurial
MySQL
P4
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Integrations
AWS Fargate
Apache Parquet
Apache Spark
Apache Tomcat
C
Django
Docker
Mercurial
MySQL
P4
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Integrations
AWS Fargate
Apache Parquet
Apache Spark
Apache Tomcat
C
Django
Docker
Mercurial
MySQL
P4
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