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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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.

Description

Timeplus is an efficient, user-friendly stream processing platform that is both powerful and affordable. It comes packaged as a single binary, making it easy to deploy in various environments. Designed for data teams across diverse sectors, it enables the quick and intuitive processing of both streaming and historical data. With a lightweight design that requires no external dependencies, Timeplus offers comprehensive analytic capabilities for streaming and historical data. Its cost is just a fraction—1/10—of what similar open-source frameworks charge. Users can transform real-time market and transaction data into actionable insights seamlessly. The platform supports both append-only and key-value streams, making it ideal for monitoring financial information. Additionally, Timeplus allows the creation of real-time feature pipelines effortlessly. It serves as a unified solution for managing all infrastructure logs, metrics, and traces, which are essential for maintaining observability. Timeplus also accommodates a broad array of data sources through its user-friendly web console UI, while providing options to push data via REST API or to create external streams without the need to copy data into the platform. Overall, Timeplus offers a versatile and comprehensive approach to data processing for organizations looking to enhance their operational efficiency.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 Yes 
Apache Kafka Yes 
Apache Parquet Yes 
ClickHouse Yes 
JSON Yes 
Python Yes 
Slack Yes 
Snowflake Yes 
Terraform Yes 
Amazon DocumentDB Yes 
Amazon DynamoDB Yes 
Amazon Web Services (AWS) No 
Databricks Yes 
DuckDB Yes 
Google Cloud Platform No 
Google Cloud SQL Yes 
MariaDB Yes 
Oracle Database Yes 
Redis Yes 
StreamNative No 

Integrations

Amazon S3 Yes 
Apache Kafka Yes 
Apache Parquet Yes 
ClickHouse Yes 
JSON Yes 
Python Yes 
Slack Yes 
Snowflake Yes 
Terraform Yes 
Amazon DocumentDB No 
Amazon DynamoDB No 
Amazon Web Services (AWS) Yes 
Databricks No 
DuckDB No 
Google Cloud Platform Yes 
Google Cloud SQL No 
MariaDB No 
Oracle Database No 
Redis No 
StreamNative Yes 

Pricing Details

$600 per month
Free Trial Yes 
Free Version No 

Pricing Details

$199 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) Yes 
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) Yes 
In Person No 

Vendor Details

Company Name

Streamkap

Founded

2022

Country

United States

Website

streamkap.com

Vendor Details

Company Name

Timeplus

Website

www.timeplus.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 

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