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ease
features
design
support

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Write a Review

Description

Scale from zero to millions of events per second effortlessly. Arroyo is delivered as a single, compact binary, allowing for local development on MacOS or Linux, and seamless deployment to production environments using Docker or Kubernetes. As a pioneering stream processing engine, Arroyo has been specifically designed to simplify real-time processing, making it more accessible than traditional batch processing. Its architecture empowers anyone with SQL knowledge to create dependable, efficient, and accurate streaming pipelines. Data scientists and engineers can independently develop comprehensive real-time applications, models, and dashboards without needing a specialized team of streaming professionals. By employing SQL, users can transform, filter, aggregate, and join data streams, all while achieving sub-second response times. Your streaming pipelines should remain stable and not trigger alerts simply because Kubernetes has chosen to reschedule your pods. Built for modern, elastic cloud infrastructures, Arroyo supports everything from straightforward container runtimes like Fargate to complex, distributed setups on Kubernetes, ensuring versatility and robust performance across various environments. This innovative approach to stream processing significantly enhances the ability to manage data flows in real-time applications.

Description

Streamkap is a modern streaming ETL platform built on top of Apache Kafka and Flink, designed to replace batch ETL with streaming in minutes. It enables data movement with sub-second latency using change data capture for minimal impact on source databases and real-time updates. The platform offers dozens of pre-built, no-code source connectors, automated schema drift handling, updates, data normalization, and high-performance CDC for efficient and low-impact data movement. Streaming transformations power faster, cheaper, and richer data pipelines, supporting Python and SQL transformations for common use cases like hashing, masking, aggregations, joins, and unnesting JSON. Streamkap allows users to connect data sources and move data to target destinations with an automated, reliable, and scalable data movement platform. It supports a broad range of event and database sources.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Flink Yes 
Apache Kafka Yes 
Apache Parquet Yes 
JSON Yes 
PostgreSQL Yes 
Python Yes 
Redis Yes 
AWS Fargate Yes 
Amazon Kinesis Yes 
Amazon S3 No 
ClickHouse No 
Delta Lake Yes 
Docker Yes 
DuckDB No 
IBM Db2 No 
Kubernetes Yes 
OpenSearch No 
Oracle Database No 
SQL Server No 
Terraform No 

Integrations

Apache Flink Yes 
Apache Kafka Yes 
Apache Parquet Yes 
JSON Yes 
PostgreSQL Yes 
Python Yes 
Redis Yes 
AWS Fargate No 
Amazon Kinesis No 
Amazon S3 Yes 
ClickHouse Yes 
Delta Lake No 
Docker No 
DuckDB Yes 
IBM Db2 Yes 
Kubernetes No 
OpenSearch Yes 
Oracle Database Yes 
SQL Server Yes 
Terraform Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$600 per month
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Arroyo

Country

United States

Website

www.arroyo.dev/

Vendor Details

Company Name

Streamkap

Founded

2022

Country

United States

Website

streamkap.com

Product Features

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Alternatives

Alternatives

Apache Kafka Reviews

Apache Kafka

The Apache Software Foundation