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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Amazon Managed Streaming for Apache Kafka (Amazon MSK) simplifies the process of creating and operating applications that leverage Apache Kafka for handling streaming data. As an open-source framework, Apache Kafka enables the construction of real-time data pipelines and applications. Utilizing Amazon MSK allows you to harness the native APIs of Apache Kafka for various tasks, such as populating data lakes, facilitating data exchange between databases, and fueling machine learning and analytical solutions. However, managing Apache Kafka clusters independently can be quite complex, requiring tasks like server provisioning, manual configuration, and handling server failures. Additionally, you must orchestrate updates and patches, design the cluster to ensure high availability, secure and durably store data, establish monitoring systems, and strategically plan for scaling to accommodate fluctuating workloads. By utilizing Amazon MSK, you can alleviate many of these burdens and focus more on developing your applications rather than managing the underlying infrastructure.

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 

Screenshots View All

Screenshots View All

Integrations

5X Yes 
Amazon Data Firehose Yes 
Amazon EC2 Yes 
Apache Kafka Yes 
Apache Spark No 
Argonaut Yes 
Azure Databricks No 
Datadog Yes 
Elastic Cloud No 
Lenses Yes 
MongoDB No 
New Relic Yes 
Onehouse Yes 
Oracle Fusion Cloud ERP No 
Presto No 
Protegrity Yes 
Snowflake No 
Sumo Logic Yes 
TensorFlow No 
Tenzir Yes 

Integrations

5X No 
Amazon Data Firehose No 
Amazon EC2 No 
Apache Kafka No 
Apache Spark Yes 
Argonaut No 
Azure Databricks Yes 
Datadog No 
Elastic Cloud Yes 
Lenses No 
MongoDB Yes 
New Relic No 
Onehouse No 
Oracle Fusion Cloud ERP Yes 
Presto Yes 
Protegrity No 
Snowflake Yes 
Sumo Logic No 
TensorFlow Yes 
Tenzir No 

Pricing Details

$0.0543 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 No 
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 Yes 
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

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/msk/

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 

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