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Description
Condense, developed by Zeliot, is a comprehensive real-time data streaming solution that integrates fully managed Apache Kafka with all necessary components to create and operate event-driven applications seamlessly. By providing a unified platform, teams can avoid the hassle of integrating multiple tools, as Condense offers managed Kafka clusters, customizable transforms, deployment pipelines, and monitoring capabilities, all securely hosted within their chosen cloud environment (AWS, Azure, or GCP) to ensure data remains protected. Additionally, Condense features Vapr, an autonomous AI supervisor designed to manage specialized agents for tasks related to Kafka, Kubernetes, Grafana, and coding, significantly reducing the operational burden associated with maintaining streaming infrastructure. Proven in demanding production settings, Condense effectively supports various industries such as connected vehicle platforms, automotive OEM telematics, electric vehicle fleets, logistics, travel and hospitality, healthcare, and fintech, processing billions of events daily and showcasing its reliability and efficiency across diverse applications. The platform's ability to streamline event-driven processes while ensuring security makes it an invaluable asset for organizations aiming to harness real-time data effectively.
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
No images available
Integrations
Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
PyTorch
SAP ERP
Snowflake
TensorFlow
Integrations
Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
PyTorch
SAP ERP
Snowflake
TensorFlow
Pricing Details
$40/month
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
Zeliot
Founded
2018
Country
India
Website
www.zeliot.in
Vendor Details
Company Name
EMQ
Founded
2013
Country
United States
Website
hstream.io
Product Features
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
Alternatives
No Alternatives