Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Data processing that integrates both streaming and batch operations while being serverless, efficient, and budget-friendly. It offers a fully managed service for data processing, ensuring seamless automation in the provisioning and administration of resources. With horizontal autoscaling capabilities, worker resources can be adjusted dynamically to enhance overall resource efficiency. The innovation is driven by the open-source community, particularly through the Apache Beam SDK. This platform guarantees reliable and consistent processing with exactly-once semantics. Dataflow accelerates the development of streaming data pipelines, significantly reducing data latency in the process. By adopting a serverless model, teams can devote their efforts to programming rather than the complexities of managing server clusters, effectively eliminating the operational burdens typically associated with data engineering tasks. Additionally, Dataflow’s automated resource management not only minimizes latency but also optimizes utilization, ensuring that teams can operate with maximum efficiency. Furthermore, this approach promotes a collaborative environment where developers can focus on building robust applications without the distraction of underlying infrastructure concerns.
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
No
API Access
Has API
Yes
Integrations
Amazon DynamoDB
No
Azure Data Lake
No
Azure Database for MySQL
No
CockroachDB
No
Databricks
No
DuckDB
No
Elasticsearch
No
Google Cloud BigQuery
No
Google Cloud IoT Core
Yes
Google Cloud Managed Service for Apache Airflow
Yes
Integrations
Amazon DynamoDB
Yes
Azure Data Lake
Yes
Azure Database for MySQL
Yes
CockroachDB
Yes
Databricks
Yes
DuckDB
Yes
Elasticsearch
Yes
Google Cloud BigQuery
Yes
Google Cloud IoT Core
No
Google Cloud Managed Service for Apache Airflow
No
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
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
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
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/dataflow
Vendor Details
Company Name
Streamkap
Founded
2022
Country
United States
Website
streamkap.com
Product Features
Streaming Analytics
Data Enrichment
Yes
Data Wrangling / Data Prep
Yes
Multiple Data Source Support
Yes
Process Automation
Yes
Real-time Analysis / Reporting
Yes
Visualization Dashboards
Yes
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