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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

A streaming database is specifically designed to efficiently ingest, store, process, and analyze large volumes of data streams. This advanced data infrastructure integrates messaging, stream processing, and storage to enable real-time value extraction from your data. It continuously handles vast amounts of data generated by diverse sources, including sensors from IoT devices. Data streams are securely stored in a dedicated distributed streaming data storage cluster that can manage millions of streams. By subscribing to topics in HStreamDB, users can access and consume data streams in real-time at speeds comparable to Kafka. The system also allows for permanent storage of data streams, enabling users to replay and analyze them whenever needed. With a familiar SQL syntax, you can process these data streams based on event-time, similar to querying data in a traditional relational database. This functionality enables users to filter, transform, aggregate, and even join multiple streams seamlessly, enhancing the overall data analysis experience. Ultimately, the integration of these features ensures that organizations can leverage their data effectively and make timely decisions.

Description

Kafma serves as a desktop GUI client and integrated development environment for Kafka, compatible with macOS, Windows, and Linux. It consolidates the consume–inspect–produce workflow into a single interface, enabling developers to effortlessly browse topics, review records, modify payloads, and send messages without the need to change views. Additionally, Kafma automatically interprets Avro and Protobuf formats, allows for message replaying and forwarding, and provides tools for drafting, comparing, and validating schemas prior to publication. Users can also oversee topics and consumer groups, monitor lag, and reset offsets as needed. The Pro version of Kafma offers the ability to replicate remote topics—including their configurations, schemas, and a specified range of messages—into a local cluster for thorough testing, with an option for field masking. Furthermore, Kafma is compatible with self-hosted Kafka instances, Confluent Cloud, and Amazon MSK, with a Free plan also being accessible for users. This versatility makes Kafma a valuable tool for developers working with Kafka environments.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Kafka
Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
PyTorch
SAP ERP
Snowflake
TensorFlow

Integrations

Apache Kafka
Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
PyTorch
SAP ERP
Snowflake
TensorFlow

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$299/year/user
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

EMQ

Founded

2013

Country

United States

Website

hstream.io

Vendor Details

Company Name

Karma IO LLC

Founded

2026

Country

United States

Website

kafma.app

Product Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Product Features

IDE

Code Completion
Compiler
Cross Platform Support
Debugger
Drag and Drop UI
Integrations and Plugins
Multi Language Support
Project Management
Text Editor / Code Editor

Alternatives

Alternatives

Apache Kafka Reviews

Apache Kafka

The Apache Software Foundation
ksqlDB Reviews

ksqlDB

Confluent
kPow Reviews

kPow

Factor House
Amazon MSK Reviews

Amazon MSK

Amazon