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features
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support

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Description

Event Hubs provides a fully managed service for real-time data ingestion that is easy to use, reliable, and highly scalable. It enables the streaming of millions of events every second from various sources, facilitating the creation of dynamic data pipelines that allow businesses to quickly address challenges. In times of crisis, you can continue data processing thanks to its geo-disaster recovery and geo-replication capabilities. Additionally, it integrates effortlessly with other Azure services, enabling users to derive valuable insights. Existing Apache Kafka clients can communicate with Event Hubs without requiring code alterations, offering a managed Kafka experience while eliminating the need to maintain individual clusters. Users can enjoy both real-time data ingestion and microbatching on the same stream, allowing them to concentrate on gaining insights rather than managing infrastructure. By leveraging Event Hubs, organizations can rapidly construct real-time big data pipelines and swiftly tackle business issues as they arise, enhancing their operational efficiency.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Abstract Security
Apache Spark
Azure Databricks
Azure Marketplace
Cogent DataHub
EMnify
Edge Delta
Evvox
LOGIQ
MongoDB
Observo AI
Onum
PeerDB
Presto
PyTorch
SAP ERP
Samza
Snowflake
TensorFlow
TriggerMesh

Integrations

Abstract Security
Apache Spark
Azure Databricks
Azure Marketplace
Cogent DataHub
EMnify
Edge Delta
Evvox
LOGIQ
MongoDB
Observo AI
Onum
PeerDB
Presto
PyTorch
SAP ERP
Samza
Snowflake
TensorFlow
TriggerMesh

Pricing Details

$0.03 per hour
Free Trial
Free Version

Pricing Details

Free
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

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/services/event-hubs/

Vendor Details

Company Name

EMQ

Founded

2013

Country

United States

Website

hstream.io

Product Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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

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