Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
PartiQL extends SQL in a manner that is straightforward, allowing nested data to be treated as integral components and enabling a smooth integration with SQL itself. This capability facilitates intuitive operations such as filtering, joining, and aggregating various types of data, including structured, semistructured, and nested datasets. By decoupling the syntax and semantics of queries from the actual data format or storage system, PartiQL provides a cohesive querying experience across diverse data stores and formats. It empowers users to engage with data irrespective of the presence of a standard schema. Additionally, the components of PartiQL—including its syntax, semantics, embedded reference interpreter, command-line interface, testing framework, and associated tests—are distributed under the Apache License, version 2.0. This licensing grants users the freedom to use, modify, and share their contributions while adhering to their preferred terms. Thus, the overall design of PartiQL enhances accessibility and flexibility in data management across various platforms.
API Access
Has API
API Access
Has API
Integrations
AWS IoT
Amazon DynamoDB
Amazon Quantum Ledger Database (QLDB)
Amazon Redshift
Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
Integrations
AWS IoT
Amazon DynamoDB
Amazon Quantum Ledger Database (QLDB)
Amazon Redshift
Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
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
PartiQL
Website
partiql.org
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
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