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What is VeloDB?

VeloDB, powered by Apache Doris, is an innovative data warehouse tailored for swift analytics on extensive real-time data streams. It incorporates both push-based micro-batch and pull-based streaming data ingestion processes that occur in just seconds, along with a storage engine that supports real-time upserts, appends, and pre-aggregations, resulting in outstanding performance for serving real-time data and enabling dynamic interactive ad-hoc queries. VeloDB is versatile, handling not only structured data but also semi-structured formats, and it offers capabilities for both real-time analytics and batch processing, catering to diverse data needs. Additionally, it serves as a federated query engine, facilitating easy access to external data lakes and databases while integrating seamlessly with internal data sources. Designed with distribution in mind, the system guarantees linear scalability, allowing users to deploy it either on-premises or as a cloud service, which ensures flexible resource allocation according to workload requirements, whether through the separation or integration of storage and computation components. By capitalizing on the benefits of the open-source Apache Doris, VeloDB is compatible with the MySQL protocol and various functions, simplifying integration with a broad array of data tools and promoting flexibility and compatibility across a multitude of environments. This adaptability makes VeloDB an excellent choice for organizations looking to enhance their data analytics capabilities without compromising on performance or scalability.

What is Streamkap?

Streamkap is an innovative streaming ETL platform that leverages Apache Kafka and Flink, aiming to swiftly transition from batch ETL processes to streaming within minutes. It facilitates the transfer of data with a latency of mere seconds, utilizing change data capture to minimize disruptions to source databases while providing real-time updates. The platform boasts numerous pre-built, no-code connectors for various data sources, automatic management of schema changes, updates, normalization of data, and efficient high-performance CDC for seamless data movement with minimal impact. With the aid of streaming transformations, it enables the creation of faster, more cost-effective, and richer data pipelines, allowing for Python and SQL transformations that cater to prevalent tasks such as hashing, masking, aggregating, joining, and unnesting JSON data. Furthermore, Streamkap empowers users to effortlessly connect their data sources and transfer data to desired destinations through a reliable, automated, and scalable data movement framework, and it accommodates a wide array of event and database sources to enhance versatility. As a result, Streamkap stands out as a robust solution tailored for modern data engineering needs.

Media

Media

Integrations Supported

Apache Flink
Apache Kafka
MySQL
Amazon DynamoDB
Amazon Redshift
Apache Iceberg
Apache Parquet
Azure Data Lake
Azure Database for MySQL
Databricks
DuckDB
Google Cloud BigQuery
IBM Db2
MariaDB
MongoDB
MotherDuck
PostgreSQL
Slack
Terraform

Integrations Supported

Apache Flink
Apache Kafka
MySQL
Amazon DynamoDB
Amazon Redshift
Apache Iceberg
Apache Parquet
Azure Data Lake
Azure Database for MySQL
Databricks
DuckDB
Google Cloud BigQuery
IBM Db2
MariaDB
MongoDB
MotherDuck
PostgreSQL
Slack
Terraform

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$600 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

VeloDB

Date Founded

2023

Company Location

Singapore

Company Website

www.velodb.io

Company Facts

Organization Name

Streamkap

Date Founded

2022

Company Location

United States

Company Website

streamkap.com

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Popular Alternatives

Apache Doris Reviews & Ratings

Apache Doris

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Apache Kafka Reviews & Ratings

Apache Kafka

The Apache Software Foundation