Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
No
API Access
Has API
No
Integrations
5X
Yes
Abstract Security
Yes
Apache Spark
No
Ascend
Yes
Azure Marketplace
Yes
Cogent DataHub
Yes
EMnify
Yes
Edge Delta
Yes
MongoDB
No
New Relic
Yes
Integrations
5X
No
Abstract Security
No
Apache Spark
Yes
Ascend
No
Azure Marketplace
No
Cogent DataHub
No
EMnify
No
Edge Delta
No
MongoDB
Yes
New Relic
No
Pricing Details
$0.03 per hour
Free Trial
No
Free Version
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
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)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
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
No
Data Wrangling / Data Prep
No
Multiple Data Source Support
No
Process Automation
No
Real-time Analysis / Reporting
No
Visualization Dashboards
No
Product Features
Database
Backup and Recovery
No
Creation / Development
No
Data Migration
No
Data Replication
No
Data Search
No
Data Security
No
Database Conversion
No
Mobile Access
No
Monitoring
No
NOSQL
No
Performance Analysis
No
Queries
No
Relational Interface
No
Virtualization
No