Streaming Analytics Software
Top Rated Products
(1-1 of 1)
The Tealium Customer Data Hub powers capabilities across the data supply chain. Tealium universally collects customer data from any source including; websites, mobile applications, devices, kiosks, servers, and files. Data collected is then standardized in the data layer, which drives…
All Products
(26-50 of 52)
Guavus SQLstream, developed by the company SQLstream that was acquired by Guavus in early 2019, is a streaming analytics platform for high throughput data, supporting a variety of streaming sources, data discovery, data wrangling, real-time threat detection and analytics.
TCS Digital Software & Solutions developed the TCS Connected Intelligence Platform (CIP) as a unified data analytics platform that enables business and technical stakeholders to harness multi-domain data from across the organization to gain a competitive advantage faster, and at…
GeoShield helps transform agencies into Real-Time Crime Centers. A CJIS-compliant solution, GeoShield connects multiple information sources such as Agency Data, Law Enforcement Data, and Live Video Streams in real-time to acquire a holistic view of all events & incidents happening…
SAS Event Stream Processing is a real-time streaming data analytics platform supporting high throughput workflows and processes such as IoT, sensors, and other transactions.
Jet-Stream is a multi-CDN streaming platform for leading broadcasters, publishers, sports clubs, events, studios, video producers and brands. Jet-Stream’s multi-CDN integration enables availability, performance and scalability with active request routing (no DNS lag) and intelligent…
Luna Streaming consists of a free, production-ready distribution of Apache Pulsar, tools and optional enterprise-class support. The solution aims to provide peace of mind with live support and expertise from a dedicated staff of engineers who are experts at operating distributed…
Oracle supports streaming analytics needs with Oracle Stream Analytics, currently in its 18th edition.
Apache Pinot is an open-source realtime distributed OLAP datastore, designed to answer OLAP queries with low latency.
Panopticon, from Altair, lets business users build, modify, and deploy sophisticated streaming analytics and data visualization applications using a drag-and-drop interface. They can connect to virtually any data source, including real-time streaming feeds and time series databases,…
Apama Streaming Analytics is a platform for streaming analytics and intelligent automated action on fast-moving big data. Combining event processing, messaging, in-memory data management and visualization, this platform is presented as a complete solution to turn relentless data…
StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. Based on Apache Pinot, StarTree Cloud integrates with transactional databases and event streaming platforms, ingesting data at millions of…
EVAM is a real-time Continuous Intelligence Platform for customer journey orchestration having real-time data integration and streaming advanced analytics with ML/AI.Evam Continuous Intelligence Platform is deployed in different industries including Telco, Banking, Retail & Loyalty,…
Impetus in Los Gatos offers Gathr (formerly StreamAnalytix), a streaming analytics platform for receiving multi-structured data (NoSQL and RDBMS), messaging services, and cloud data stores, and supplying real-time actionable analytics on high velocity data.
Anomaly Detector on Microsoft's Azure is an AI service that helps foresee problems. Users can embed time-series anomaly detection capabilities into apps to help users identify problems quickly. Anomaly Detector ingests time-series data of all types and selects the best anomaly detection…
Conviva is a census, continuous measurement and engagement platform for streaming media. Powered by Conviva's Stream Sensor™ and Stream ID™, the real-time platform helps marketers, advertisers, tech ops, engineering and customer care teams to acquire, engage, monetize and retain…
Bitmovin powers OTT online video providers with video developer tools. Bitmovin's Encoding, Player and Analytics products, aim to redefine the viewer experience, while lowering streaming costs.
RisingWave is an open-source distributed SQL database for stream processing. It is designed to reduce the complexity and cost of building real-time applications. RisingWave offers users a PostgreSQL-like experience specifically tailored for distributed stream processing.
Interra Systems' BATON is a M/L and AI enabled automated QC platform that provides quality and compliance checks for VOD content, in the cloud / on-premises, for linear and streaming workflows. The hybrid QC solution implements organizational QC policy to support a combination of…
Kinetica, from the company of the same name headquartered in San Francisco, is an analytic database for fusing data across streams and data lakes to unlock value from spatial and temporal data at scale and speed. Kinetica helps companies drive outcomes from machine data that includes…
Lenses.io delivers a developer workspace for building & operating real-time applications on any Apache Kafka. By enabling teams to monitor, investigate, secure and deploy on their data platform, organizations can shift their focus to data-driven business outcomes and help engineers…
NPAW's YOUBORA Suite is a real-time video analytics platform that allows OTTs, Telcos, Media Companies and Broadcasters to translate billions of data points into actionable business insights for them to monitor, analyze, and capitalize on, all while their users are watching. In the…
Data Lake Insight (DLI) is a serverless data processing and analysis service compatible with Apache Spark, Flink, and openLooKeng (Presto-based) ecosystems. Users can perform stream, batch, and interactive analysis to query mainstream data formats without data ETL, and use standard…
Solace in Ottawa offers the Solace Cloud to support a cloud infrastructure with enterprise messaging-as-a-service to speed cloud app development in an event-driven architecture, bridge on-premise services to cloud services, and support Internet-of-Things (IoT) applications.
Cloudera DataFlow (CDF), formerly Hortonworks DataFlow (HDF), is a scalable, real-time streaming analytics platform that ingests, curates, and analyzes data for key insights and immediate actionable intelligence. It is designed to process real-time data streaming at high volume and…
Hazelcast is a real-time, intelligent application platform that enables enterprises to capture value at every moment by consolidating transactional, operational and analytical workloads into a single data platform.
Learn More About Streaming Analytics Software
What is Streaming Analytics?
Streaming analytics software processes and analyzes fast-moving live and historical data to raise alerts, make decisions, and report findings in real-time without human intervention. Streaming analytics can gather insights from multiple sources of data, such as applications, mobile devices, and machines. Because of this, they can determine threats or opportunities, address them quickly, and create protocols to address similar events in the future. Since streaming analytics can almost instantly acknowledge and address patterns in large volumes of information from many sources, it is useful for the rapid analysis of real-time data. This can include data from Internet of Things (IoT) sensors, medical monitoring equipment, and internal financial transactions.
For example, if you have a network that you need to monitor, there is a list of things that need to be managed - temperature of important hardware, connection to the internet, ongoing security programs, and so forth. Streaming analytics will capture data from all of these sources, recognize patterns, and address irregularities. If there is an issue with the network - a security protocol is suddenly disabled, for instance - streaming analytics will instantly and autonomously determine the source of the issue, create a course of action based on the most appropriate response, and use this information to detect possible threats in the future.
Streaming analytics solutions are similar to complex event processing (CEP) software, but they provide more general support for such as storage, monitoring, analysis, visualization, modeling, message queuing, and processing for batch and aggregate data without the need for correlation calculation with CEP. This enables a simpler user experience by removing the need to consider event correlation. Additionally, compared to CEP, streaming analytics tend to have better support for parallel processing, which sees data broken up into ‘chunks” that are processed and analyzed simultaneously.
Streaming Analytics Features
These are the most common features among streaming analytics solutions:
- Proactive monitoring
- Security monitoring
- Parallel processing
- Fault-tolerant processing
- Integrated machine learning capabilities
- Batch processing
- Big Data streaming.
- Asynchronous data messaging
- Compatibility with multiple data sources
- Data archiving and retention
- Data migration and integration
- Data masking
- Data aggregation
- Data virtualization
- Data analysis
- Data reporting and visualization
- Disaster recovery
- Audit trails
- Hierarchical modeling
- Query framework
- Datastream customization and blending
- Integrated dashboard
- Cloud, browser, or on-premise hosting
Streaming Analytics Comparison
When comparing streaming analytics solutions, consider the following:
Open-source vs. monitored platforms. Open-source streaming analytics solutions like Apama Community Edition have a wide range of benefits for small businesses, including personalization, flexibility, compatibility with other solutions, and low cost. However, their installation, integration, management, and troubleshooting are handled by the end-user, meaning they may require a bit more time and effort from your IT department. Monitored platforms like Amazon Kinesis and Google Cloud DataFlow manage the major responsibilities of maintaining streaming analytics in exchange for increased cost, more limited personalization, and removal of some control (namely server uptime) from the end-user.
Structured vs. unstructured data processing. Structured data refers to data that is specific and stored in predefined formatting, whereas unstructured data is varied and stored in its native formatting. The type of data you expect to handle will determine the best solution for you, as some streaming analytics may not perform as well with unstructured data, which in turn may impact overall performance. IBM Streaming Analytics and SAS Event Stream Processing boast robust support for handling both structured and unstructured data streams.
Telemetry analysis. If you intend to use streaming analytics to monitor data from the Internet of Things, you’ll need a solution that can process the telemetry data coming from sensors, cameras, and other real-world measurement devices. Oracle Stream Analytics and IBM Streaming Analytics offer geospatial analysis solutions.
Fault-tolerance processing. The degree to which streaming analytics software handles faults within datastreams - fragmented data, read failure, low latency, and so forth - will determine which solution works best for you. This is especially true if your business handles time-sensitive data, as fault-tolerance can increase overall processing time. Flink and Kafka have robust auto-restart analysis features, making them efficient in their fault tolerance.
Programming language. Finally, streaming analytics solutions may have limited ranges of programming languages that they can use to create or develop real-time analytics. Java is universally supported, but if you require support for more specific languages, you’ll need to ensure a solution can work with it. For example, Azure Stream Analytics leverage C# and SQL, whereas IBM Stream Analytics can support Python and Scala.
Pricing Information
There are many free, open-source streaming analytics solutions. For paid solutions, prices can range between $15 to $200 a month at the lowest subscription cost, with possible variation based on the amount of data processed. These vendors also offer free trials or low-cost price plans with limited features. Vendors should be contacted directly for price points.
More Resources
If you need more information about structured and unstructured data, this resource will be helpful for you: