mostly on major arterials and highways. DOT uses this information for emergency response and management.The metadata defines the fields available in this data feed and explains more about the data.

We receive a large flux of several 1000 real-time ticks per second from multiple sources across over 2000 currency pairs. From this raw data, Olsen computes and publishes a fixing every second, which is a reasonably tradable median level Bid and Ask.

We are a neutral data provider and not a broker or trading platform. Our fixing is therefore used by many traders to check their broker prices and minimize execution risk.

Find unrivaled company, commodity and economic stories formatted for automated consumption, with LSEG Real-Time News, powered by Reuters.

Iowa Department of Transportation's Intelligent Transportation System (ITS) Detector Sensors. Sensor Feed: Includes location of sensors, current travel speed, traffic counts, occupancy counts, and more.Work Zone Alert Feed: Includes work zones that have dropped below the normal speed and are determined to have a critical traffic speed abnormality.

Sports Data Low-Latency Feed Market Outlook

According to our latest research for 2024, the global sports data low-latency feed market size stands at USD 1.47 billion. The market is experiencing robust growth, propelled by the increasing demand for real-time data delivery across various sports-related applications. The market is set to expand at a CAGR of 18.2% during the forecast period, reaching an estimated USD 6.45 billion by 2033. This growth is primarily driven by the rapid adoption of digital transformation in the sports industry, the surge in sports betting activities, and the proliferation of live streaming and fantasy sports platforms. As per our latest research, the sports data low-latency feed market is positioned for significant evolution, with technological advancements and increasing integration of artificial intelligence playing pivotal roles in shaping the industry landscape.

A major growth factor for the sports data low-latency feed market is the escalating demand for instant access to accurate sports information. With the rise of live sports broadcasting and the surge in in-play betting, stakeholders across the sports ecosystem require ultra-fast data feeds to ensure timely and precise delivery of critical match events, player statistics, and video content. This demand is further amplified by the expectations of modern sports fans, who seek real-time engagement and interactive experiences through various digital platforms. The integration of advanced data analytics and machine learning algorithms has enabled providers to deliver highly reliable and actionable insights, thereby enhancing the value proposition for end-users such as broadcasters, betting companies, and sports leagues. Consequently, the ability to provide low-latency data feeds has become a key differentiator in the competitive sports data market.

The proliferation of sports betting and fantasy sports platforms globally has significantly contributed to the growth of the sports data low-latency feed market. These platforms rely heavily on real-time data to facilitate seamless user experiences, minimize the risk of arbitrage, and ensure regulatory compliance. The legalization of sports betting in several jurisdictions, particularly in North America and Europe, has led to a surge in demand for high-speed, accurate data feeds that support dynamic odds calculation and in-play wagering. Furthermore, the increasing popularity of fantasy sports leagues has created new avenues for data feed providers to deliver comprehensive player statistics, match updates, and video highlights, all in real time. As the competitive landscape intensifies, companies are investing in advanced infrastructure and partnerships to enhance their data delivery capabilities and expand their market presence.

Technological advancements in network infrastructure, such as the deployment of 5G and edge computing, have played a crucial role in driving the sports data low-latency feed market forward. These technologies enable faster data transmission, reduced latency, and improved reliability, which are essential for delivering real-time sports content to a global audience. The adoption of cloud-based solutions has further facilitated scalability and flexibility, allowing stakeholders to manage large volumes of data efficiently and cost-effectively. Moreover, the integration of video analytics and artificial intelligence has opened new possibilities for automated content generation, personalized recommendations, and enhanced fan engagement. As the industry continues to evolve, the convergence of these technologies is expected to unlock new growth opportunities and redefine the standards for real-time sports data delivery.

Regionally, North America dominates the sports data low-latency feed market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The strong presence of major sports leagues, advanced technological infrastructure, and the rapid adoption of sports betting and fantasy sports platforms have positioned North America as the leading market. Europe is also experiencing significant growth, driven by the increasing popularity of football and the expansion of regulated betting markets. Asia Pacific is emerging as a high-growth region, fueled by rising sports viewership, digital transformation initiatives, and the growing adoption of cloud-based solutions. Latin America and the Middle East & Africa are witnessing steady growth, supported by investments in sports infrastructure and increasing internet penetration. The regional outlook for the mar

Streaming Analytics Market Outlook

According to our latest research, the global streaming analytics market size reached USD 19.2 billion in 2024, driven by accelerated digital transformation across industries and the surging need for real-time data analysis. The market is exhibiting robust momentum, with a recorded CAGR of 25.7% from 2025 to 2033. Based on this growth trajectory, the streaming analytics market is forecasted to achieve a value of USD 143.2 billion by 2033. The primary growth factor propelling this expansion is the increasing demand for advanced analytics solutions that can process and analyze large volumes of data in real time, enabling organizations to make faster, data-driven decisions.

A major driver fueling the growth of the streaming analytics market is the exponential rise in data generated from connected devices, IoT sensors, social media, and enterprise applications. Organizations across sectors are recognizing the competitive advantage of leveraging streaming analytics to monitor operations, detect anomalies, and respond proactively to business events as they unfold. The ability to harness real-time insights has become essential in high-stakes environments such as financial services for fraud detection, telecommunications for network optimization, and manufacturing for predictive maintenance. The proliferation of 5G networks and the expansion of cloud computing infrastructure have further accelerated the adoption of streaming analytics platforms by providing the necessary bandwidth and computational power to process massive data streams with minimal latency.

Another significant growth factor is the integration of artificial intelligence (AI) and machine learning (ML) technologies with streaming analytics solutions. These advanced capabilities enable organizations to move beyond traditional descriptive analytics toward predictive and prescriptive analytics, uncovering actionable insights from live data feeds. The demand for real-time analytics is also being amplified by the increasing adoption of edge computing, which allows data to be processed closer to its source, reducing response times and improving decision-making efficiency. As organizations continue to invest in digital transformation initiatives, the need to analyze data as it is generated—rather than after it is stored—has become a critical differentiator for operational agility and customer experience.

The streaming analytics market is also benefitting from the growing emphasis on regulatory compliance and risk management. In highly regulated industries such as banking, healthcare, and energy, organizations are leveraging streaming analytics to monitor transactions, detect suspicious activities, and ensure compliance with evolving regulatory requirements. The ability to analyze data in real time not only helps in mitigating risks but also supports proactive incident response and reporting. Furthermore, the increasing focus on customer-centricity in retail and e-commerce is driving the adoption of streaming analytics to personalize marketing efforts, optimize inventory, and enhance overall service delivery. These factors collectively underscore the market’s strong growth outlook through the forecast period.

Regionally, North America continues to dominate the streaming analytics market, accounting for the largest share in 2024 due to the presence of leading technology providers, rapid adoption of advanced analytics solutions, and substantial investments in cloud infrastructure. However, the Asia Pacific region is emerging as the fastest-growing market, driven by the digitalization of enterprises, expanding e-commerce sector, and government initiatives supporting smart cities and IoT deployments. Europe maintains a strong position, particularly in sectors such as BFSI and manufacturing, while Latin America and the Middle East & Africa are witnessing steady growth as organizations in these regions increasingly recognize the value of real-time data analytics. This global expansion highlights the universal relevance of streaming analytics across industries and geographies.

Component

COTrip.org has a real-time travel data feed provided by Intelligent Transportation Systems (ITS), a division of CDOT, for data including Road Conditions, Speeds, Travel Times, etc.

Once you have a username and password, you access individual XML feeds by forming your URL like this:

Form your URL like this: https://username:password@data.cotrip.org/xml/cameras.xml

For example.

These data are a subset of the WaveNet near real time data feed, consisting of telemetry (automatically transmitted data) from the Cefas operated Directional Wave Riders (DWR) within UK waters over the past 48 hours. As this is a near-live feed, the data provided have not been fully quality checked or assured and hence should be used with due caution.

GTFS Realtime feeds have been provided by the Victoria Department of Transport and Planning

to provide realtime updates about Public Transport services. It contains feeds about:

• Trip Updates \- delays, cancellations, changed routes
• Service Alerts \- stop moved, unforeseen events affecting a station, route or the entire network
• Vehicle Positions \- information about the vehicles including location and congestion level

Please note these feeds are provided in the Protocol Buffer format and are not human readable.

For more information refer to this GTFS Realtime page (https://gtfs.org/realtime/) which is maintained by MobilityData (https://mobilitydata.org/) and facilitates the GTFS and GTFS\-R specification.

API Key \- To obtain an API Key please continue to signup using our old Data Exchange Platform (TEMPORARY)

Summary of Changes

GTFS\-R \- Trip Updates \- Metro Train: Schedule Relationships, Stop ID, and Route ID have been added as additional fields to enhance real\-time trip accuracy.

GTFS\-R \- Vehicle Positions \- Metro Train: Route ID added as a Conditionally Required field to improve data details.

GTFS\-R \- Service Alerts \- Metro Train: Additional information about planned and unplanned disruptions have been added to include more details about delays and bus replacement services. Route ID and Direction ID are two new fields that have been added also.

Please note: the information in the current ‘Required’ data fields remains the same and data feeds continue to follow the GTFS Realtime global standards and specifications. These data feeds will also still be hosted via the Data Exchange Platform, so there are no changes to API keys. However, in the next few months, they will be moved to the Transport Victoria Open Data Portal and users will need to register for a new API key. We will provide more information closer to the date.

Why are these changes being made?

These changes are being made to:

• Create consistent and accurate real\-time transport information for open data users.
• Improve trip planning and data usability by better aligning static and real\-time datasets.

This dataset contains 20+ years of all items in the luxury jewelry category sold on auction by Christie’s, Sotheby’s, Bonhams and Phillips from 2000 to date.

This dataset is prepared for statistical factor pricing models with contains 20+ years of gemstones sold on auction and in private sales.

Forex Symbols

Finage offers you more than 1300+ forex data as real-time.

With Finage, you can react to the forex data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 15-year historical data API.

Commodities Bonds Metals Forex You can view the full FX market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_FX_Symbol_List.pdf

Hong Kong has a lot of real-time data which are made available by the Government of Hong Kong Special Administrative Region at https://DATA.GOV.HK/ (“DATA.GOV.HK”). These data were processed and converted to Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform.These series of Operations Dashboard integrate different available real-time datasets in Hong Kong to provide a dashboard interface for monitoring real-time data feed on your desktop or tablet device. The objectives are to facilitate our Hong Kong ArcGIS Online users to view these data in a spatial ready format and save their data conversion effort.These series of Operations Dashboard come in three themes, environmental, traffic and integrated.The Environmental theme contains real-time temperature, air quality health risk and air pollution concentration of different districts in Hong Kong. Traffic theme contains real-time information of estimated journey time, car park vacancy, traffic speed of major roads, traffic snapshot images and speed map panels in Hong Kong.The integrated theme combines the above two sets of data, which are environmental and traffic, and makes them into one single dashboard view.

This dataset contains 20+ years of all items in the Wine and Whisky categories sold on auction by Christie’s, Sotheby’s, Bonhams and Phillips from 2000 to date.

Cryptocurrencies

Finage offers you more than 1700+ cryptocurrency data in real time.

With Finage, you can react to the cryptocurrency data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 7-year historical data API.

You can view the full Cryptocurrency market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_Crypto_Coverage.pdf

This dataset is prepared for statistical factor pricing models and standardized across variables including country, region, currency, vendor, and manufacturer for seamless data filtering. It contains 20+ years of aircraft and private jets sold at auction and in private markets across all categories including business jets, turboprops, helicopters, vintage aircraft, warbirds, and commercial aircraft. Tracked manufacturers include: Gulfstream, Bombardier, Cessna, Dassault Falcon, Embraer, Boeing Business Jets, Airbus Corporate Jets, Hawker Beechcraft, Citation, Learjet, Pilatus, King Air, Piper, Cirrus, Diamond, Mooney, and many other aviation manufacturers including vintage and military aircraft.

The National Transport Authority publish Realtime Passenger Information (RTPI) through the GTFS Realtime specification (https://developers.google.com/transit/gtfs-realtime). This realtime feed is provided by an API - in order to connect to this API, you will need to register an account on the NTA Developer Portal - https://developer.nationaltransport.ie The data in this feed can be used in conjunction with the GTFS Static specification to provide schedule details for the realtime data - please download the GTFS Schedule file for realtime operators.

This RSS feed provides real-time information on DOT OIG products and annoucnements that are released

This record is for Approval for Access product AfA501 for approximately 1000 automatic rainfall data from the Environment Agency rainfall API.

The data is available on an update cycle which varies across the country, typically updated daily but updated faster is rainfall is detected. This is update frequency is usually increased during times of flooding, etc.

Readings are transferred via telemetry to internal and external systems in or close to real-time.

Measurement of the rainfall is taken in millimetres (mm) accumulated over 15 minutes. Note that rainfall data is recorded in GMT, so during British Summer Time (BST) data may appear to be an hour old. Data comes from a network of over 1000 gauges across England. Data shown is raw data collected from the gauges and is subject to quality control procedures. As a result, values may change after publication on this website.

Continuous rainfall information is also stored on our hydrometric archive, Wiski, and can be provided in non real-time on request through our customer contact centre. This raw rainfall data is provided to the Met Office for quality control along with all the data from our registered daily storage gauges (c.1400). The quality controlled dataset is covered in AfA148 Quality Controlled Daily and Monthly Raingauge Data from Environment Agency Gauges.

Data from a small selection of Met Office raingauges are included in our open data feed. This data is also available from the Met Office as open data.

511 Real-Time XML Feed access request for Iowa, Minnesota, Nebraska, and other CARS511 partners.