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What is IBM Streams?

IBM Streams processes a wide range of streaming information, encompassing unstructured text, video, audio, geospatial data, and sensor inputs, which allows organizations to discover opportunities and reduce risks while making prompt decisions. Utilizing IBM® Streams, users can convert swiftly evolving data into valuable insights. This platform assesses different types of streaming data, equipping organizations to detect trends and threats as they emerge. When combined with the other features of IBM Cloud Pak® for Data, which is built on a versatile and open framework, it boosts collaboration among data scientists in crafting models suitable for stream flows. Additionally, it enables the real-time evaluation of extensive datasets, making it easier than ever to extract actionable value from your data. These capabilities empower organizations to fully leverage their data streams, leading to enhanced outcomes and strategic advantages in their operations. As a result, organizations can optimize their decision-making processes and drive innovation across various sectors.

What is HStreamDB?

A streaming database is purpose-built to efficiently process, store, ingest, and analyze substantial volumes of incoming data streams. This sophisticated data architecture combines messaging, stream processing, and storage capabilities to facilitate real-time data value extraction. It adeptly manages the continuous influx of vast data generated from various sources, including IoT device sensors. Dedicated distributed storage clusters securely retain data streams, capable of handling millions of individual streams effortlessly. By subscribing to specific topics in HStreamDB, users can engage with data streams in real-time at speeds that rival Kafka's performance. Additionally, the system supports the long-term storage of data streams, allowing users to revisit and analyze them at any time as needed. Utilizing a familiar SQL syntax, users can process these streams based on event-time, much like querying data in a conventional relational database. This powerful functionality allows for seamless filtering, transformation, aggregation, and even joining of multiple streams, significantly enhancing the overall data analysis process. With these integrated features, organizations can effectively harness their data, leading to informed decision-making and timely responses to emerging situations. By leveraging such robust tools, businesses can stay competitive in an increasingly data-driven landscape.

Media

Media

Integrations Supported

Integrations Supported

Apache Spark
Azure Databricks
Elastic Cloud
MongoDB
Oracle Fusion Cloud ERP
Presto
PyTorch
SAP ERP
Snowflake
TensorFlow

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/streaming-analytics

Company Facts

Organization Name

EMQ

Date Founded

2013

Company Location

United States

Company Website

hstream.io

Categories and Features

Data Science

Not specified

Streaming Analytics

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

Categories and Features

Database

Not specified

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