Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Discover how to enhance sales growth effortlessly by utilizing automated data pipelines that connect seamlessly to data lakes or cloud storage solutions without the need for coding. This adaptable platform adheres to industry standards, enabling the integration of sales and marketing data to generate automated insights for more intelligent expansion. Eliminate the hassle and costs associated with cumbersome manual data downloads. You’ll always have a clear understanding of your expenses, only paying for the services you actually use. Empower your tools with rapid access to data that is ready for analytics. Our certified developers prioritize security by exclusively working with official APIs. You can quickly initiate data pipelines sourced from widely-used platforms. With pre-built, pre-transformed pipelines at your disposal, you can unlock crucial data from sources like Amazon Vendor Central, Amazon Seller Central, Instagram Stories, Facebook, Amazon Advertising, Google Ads, and more. The processes for data ingestion and transformation require no coding, allowing teams to swiftly and affordably harness the full potential of their data. Your information is consistently safeguarded and securely stored in a reliable, customer-controlled data destination such as Databricks or Amazon Redshift, ensuring peace of mind as you manage your data assets. This streamlined approach not only saves time but also enhances overall operational efficiency.
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
Integrations
Amazon Redshift
Yes
Amazon S3
Yes
Azure Data Lake
Yes
Google Cloud BigQuery
Yes
Snowflake
Yes
AOL Mail
Yes
Alteryx
Yes
Apache Parquet
No
Azure Data Lake Analytics
Yes
ClickHouse
No
Integrations
Amazon Redshift
Yes
Amazon S3
Yes
Azure Data Lake
Yes
Google Cloud BigQuery
Yes
Snowflake
Yes
AOL Mail
No
Alteryx
No
Apache Parquet
Yes
Azure Data Lake Analytics
No
ClickHouse
Yes
Pricing Details
$149 per month
Free Trial
Yes
Free Version
Yes
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
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
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Openbridge
Founded
2013
Country
United States
Website
www.openbridge.com
Vendor Details
Company Name
Streamkap
Founded
2022
Country
United States
Website
streamkap.com
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No
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
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