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Top 20 Free, Open Source and Premium Stream Analytics Platforms
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Top 20 Free, Open Source and Premium Stream Analytics Platforms

Top 20 Free, Open Source and Premium Stream Analytics Platforms
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Technology has made it possible for organizations to generate more data from connected sources such as sensors and devices. More and more real-time information has become available and many organizations are using applications that generate actionable insights. With the increasing use of the cloud, applications, sensors, machines, networks, mobile devices, and the Internet of Things (IoT), organizations are looking for a way to make the most of the insights generated by real-time data. They also need to perform cloud-based stream processing in real-time. Organizations can use different tools to capture and analyze their data. The best option is to implement a high-performance platform that can analyze data in real-time. There are different types of stream analytics platforms with different features and benefits. Businesses can choose the appropriate stream analytics platform and capitalize on the different features depending on their needs.

Open Source Stream Analytics Platforms : Apache Flink, Apache Spark, Apache Samza, Apache Storm are some of theTop Open Source Stream Analytics Platforms

Top Stream Analytics Platforms : Striim, Salford Systems SPM, Cisco Connected Streaming Analytics, SAS Event Stream Processing, FICO Data Management Solutions, WSO2 Complex Event Processor, Think Enterprise Data Miner , Software AG Apama Streaming Analytics, SQLstream, Oracle Stream Analytics, IBM Streams, SAP Event Stream Processor, Azure Stream Analytics, Informatica, StreamAnalytix, TIBCO Event Processing are some of the Top Stream Analytics Platforms.

What are Stream Analytics Platforms?

Stream Analytics helps to develop and deploy solutions to gain real time insights from devices, sensors, and applications by real time stream processing in the cloud. Stream Analytics enables to perform real time analytics for Internet of Things solutions, stream millions of events per second, provide mission critical reliability and performance, also deliver real time dashboards and alerts over data from devices and applications, correlate across multiple streams of data and use SQL based language for development. Stream Analytics customers deploy and monitor streaming jobs.

Applications of stream analytics includes personalized, real-time stock-trading analysis and alerts offered by financial services companies, real-time fraud detection; data and identity protection services, analysis of data generated by sensors and actuators, web clickstream analytics, customer relationship management (CRM) alerts, supply chain alerts, transportation alerts.

Stream analytics platforms allow organizations to develop and implement solutions in order to provide insights from different sources of data such as applications, mobile devices, sensors, and machines in real-time. Organizations use these platforms to perform cloud-based stream processing and analytics for IoT in real-time. Streaming analytics enables organizations to carry out real-time analyses of data and process millions of transactions or events that conventional technologies cannot process. The most effective stream analytics platforms can perform thousands to millions of transactions or events per second. They help businesses to develop the applications needed to perform critical missions in an efficient and timely manner. Users of these platforms can also access dashboards and receive alerts in real-time based on data from applications and different devices. The alerts may come from financial service providers, stock markets, identity protection service providers, supply chains, CRM systems, and fraud detection systems. Businesses can develop real-time solutions based on the data collected and analyzed on the cloud.

What are the features of Stream Analytics Platforms?

What are the features of Stream Analytics Platforms?

The best stream analytics platforms include the following features:

  • Dashboards : Data visualization is an important component of stream analytics platforms. Dashboards make it possible to visualize data in the form of graphs, images, and tables that show the most important figures. The best dashboards allow users to dig deeper to identify problems and develop solutions.
  • Real-time Data Analysis and Reporting : Stream analytics platforms include a feature for analyzing data in motion. The most powerful platforms can process millions of transactions per second. Real-time reports enable quick responses and instant decisions.
  • Anywhere Access : Users are able to access the platform and make informed decisions regardless of their location. You don’t have to be in the office to access reports and make critical decisions.
  • Compatibility with Different Data Sources : The best stream analytics platforms are compatible with the existing systems. They can also capture data from different sources such as spreadsheets, CRM, ERP, payroll, accounting, and database systems.
  • Simplicity – This is an important feature because it ensures that anyone can use the platform regardless of their background in IT.

Stream analytics platforms have the following benefits:

  • Companies can effectively manage their key performance indicators by visualizing data in real-time.
  • Businesses can gain insight into the behaviours of their customers.
  • Businesses can become more competitive by analyzing trends, identifying threats, generating forecasts, and making critical decisions.

Top Open Source Stream Analytics Platforms

Apache Flink, Apache Spark, Apache Samza, Apache Storm are some of theTop Open Source Stream Analytics Platforms
Top Open Source Stream Analytics Platforms
PAT Index™
 
 
 
 

1.Apache Flink

Apache Flink is an open source platform for distributed stream and batch data processing. Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams. Flink includes several APIs for creating applications that use the Flink engine: DataStream API for unbounded streams embedded in Java and Scala, DataSet API for static data embedded in Java, Scala, and Python, and Table API with a SQL-like expression language embedded in Java and Scala.

Apache Flink

Apache Flink

2

Apache Spark

Apache Spark is a fast and general engine for large-scale data processing. Spark requires a cluster manager and a distributed storage system. For cluster management, Spark supports standalone (native Spark cluster), Hadoop YARN, or Apache Mesos. For distributed storage, Spark can interface with a wide variety, including Hadoop Distributed File System (HDFS), MapR File System (MapR-FS), Cassandra,OpenStack Swift, Amazon S3, Kudu, or a custom solution can be implemented. Spark also supports a pseudo-distributed local mode, usually used only for development or testing purposes, where distributed storage is not required and the local file system can be used instead, Spark is…

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Spark runs on Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources including HDFS, Cassandra, HBase, and S3. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming.

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Apache Samza

Apache Samza is a distributed stream processing framework. It uses Apache Kafka for messaging, and Apache Hadoop YARN to provide fault tolerance, processor isolation, security, and resource management. Unlike most low-level messaging system APIs, Samza provides a very simple callback-based “process message” API comparable to MapReduce. Samza manages snapshotting and restoration of a stream processor’s state. When the processor is restarted, Samza restores its state to a consistent snapshot. Samza is built to handle large amounts of state (many gigabytes per partition). Whenever a machine in the cluster fails, Samza works with YARN to transparently migrate your tasks to another…

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Samza is built to handle large amounts of state (many gigabytes per partition). Whenever a machine in the cluster fails, Samza works with YARN to transparently migrate your tasks to another machine.

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4

Apache Storm

Apache Storm is a distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more.Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Storm integrates with…

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Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more.

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Apache Storm

Top Stream Analytics Platforms Vendors

Striim, Salford Systems SPM, Cisco Connected Streaming Analytics, SAS Event Stream Processing, FICO Data Management Solutions, WSO2 Complex Event Processor, Think Enterprise Data Miner , Software AG Apama Streaming Analytics, SQLstream, Oracle Stream Analytics, IBM Streams, SAP Event Stream Processor, Azure Stream Analytics, Informatica, StreamAnalytix, TIBCO Event Processing are some of the Top Streaming Analytics Software.

Top Stream Analytics Platforms
PAT Index™
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1

Striim

Striim is an end-to-end, real-time data integration and intelligence and streaming platform. It ingest data in real-time from a wide variety of sources and it data more valuable while it's streaming before loading it to common data targets. Striim enables smart decisions by analyzing all of your data in-flight for relevancy. It is driven by customer requirements and demand. it focuses on facilitating real-time, hybrid Cloud integration, and simplifying the management of applications running on streaming data. The latest striim version include several hybrid cloud integrations with Microsoft® data solutions running on Azure®. Before data lands on SQL database striim…

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Striim is a real-time data integration and streaming analytics software platform that enables smart decisions by analyzing all of your data in-flight, while it is still relevant

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Striim

2

Salford Systems SPM

SPM Salford Predictive Modeler software suite is a highly accurate and ultra-fast analytics and data mining platform for creating predictive, descriptive, and analytical models from databases of any size, complexity, or organization. This suite of data mining tools includes Salford Systems' flagship products of CART, MARS, TreeNet, and Random Forests. Salford Systems SPM’s brainpower includes more than 70 pre packaged automated scenarios that are inspired by how leading model analysts build their work.Salford Systems SPM currently offers 4 different product versions that users can choose from depending on what they need for the company. The Basic Version provides data mining,…

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SPM software suite's automation accelerates the process of model building by conducting substantial portions of the model exploration and refinement process for the analyst.

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Salford Systems SPM

3

Cisco Connected Streaming Analytics

Cisco Connected Streaming Analytics is an analytic platform that provides organizations the ability to manage data effectively while ensuring speed and real time streaming despite multitasking. Cisco Connected Streaming Analytics support queries by processing and monitoring live data for accurate results. This also provides real time analysis that can be used to take immediate actions and decisions that would be efficient for the business.Cisco Connected Streaming Analytics’s framework is designed to be utilized by for case developments from various business and networks working on different industries. It provides real time valuable insights with bigger data views to establish events that…

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CSA’s framework and interfaces are ideal for use case development across a wide variety of business and network management functions and industries. CSA provides real-time insights with big data views to support actionable events and dynamic dashboards to help you get more value out of your data

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Cisco Connected Streaming Analytics

4

SAS Event Stream Processing

SAS Event Stream Processing provides instant information that an organization can take immediate action. With a huge amount of date flow is received, SAS Event Stream Processing allows users to make responses and actions right away before they are tagged as obsolete. View and respond to real time and high velocity of data and plan on the required action effectively.With SAS Event Stream Processing, streamed data are of quality and accuracy which give the business the opportunity to make necessary actions that are also accurate. It also provides prebuilt analytic expressions as well as advanced analytics integration for complex pattern…

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An extensive suite of source adapters helps you consume the sources you need today – including both structured and unstructured data streams – with the ability to extend in the future.

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5

FICO Data Management Solutions

FICO's Data Management Solutions’ streaming data platform aims to help organizations find the right information in making big decisions that would be beneficial to the business. With a huge data available for most companies, being able to utilize them well and gather the most relevant data is the key to be productive. This provides powerful insights derived from various sources to establish rightful decisions. FICO's Data Management Solutions collects data from structured and unstructured sources. By sing analytic processing, it gives definitive information regarding customer relationship with real time streams of data. This will then generate real time insights that…

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FICO Data Orchestrator is a component of the FICO Decision Management Suite, a cost-effective and easy way for customers to evaluate, customize, deploy and scale state-of-the-art analytics and decision management solutions.

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6

WSO2 Complex Event Processor

WSO2 Complex Event Processor is a 100% open source program that provides businesses the capability to identify valuable information or events across multiple data sources real time to their own advantage. These data can be analyzed for their possible impact and let the business act on it as soon as they are established. Manage data precisely and respond to urgent business situation that could either be beneficial or poses a risk. WSO2 Complex Event Processor is available on-premise, on top of WSO2 Private PaaS as well as any public cloud available such as Amazon AWS. WSO2 Complex Event Processor’s dashboards…

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WSO2 CEP facilitates real time event detection, correlation and notification of alerts, combined with rich visualization tools to help build monitoring dashboards.

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7

Think Enterprise Data Miner

Think Enterprise Data Miner offers a unique solution for complex business problems when it comes to managing data and understanding how analytics can help provide solution for strong decision makings. Its data mining techniques and knowledge discovery is the key for enterprises to work on their connections that needs huge amount of information in order to establish customer relations and better plans for the future. This information is gathered from various sources and is streamed real time for queries. Think Enterprise Data Miner’s predictive intelligence is provided to all its users to be able to accurately utilize them to gain…

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It combines ease-of-use with enterprise scalability to uncover latent knowledge from massive amounts of data through host applications.

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8

Software AG Apama Streaming Analytics

Software AG's Apama Streaming Analytics is a platform for streaming analytics and intelligent automated action on fast-moving big data. It includes events processing, messaging, in-data managing and visualizing working simultaneously on data streams.Software AG's Apama Streaming Analytics lets the users create an end-user business dashboard used for monitoring. Conduct tests on previously captured data streams before actual deployment. Combine data to make temporary analysis while filtering and using information that are relevant to the organization. With Software AG's Apama Streaming Analytics users will be able to predict what’s going to take place in the future; this helps the business better…

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The Apama platform allows you to analyze and act on high-volume business operations and customer interactions in real time—and identify what is likely to happen, while you can still influence the outcome.

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Software AG Apama Streaming Analytics

9

SQLstream

SQLstream gathers all types of data and be analyzed continuously from any source and format with speed. SQLstream help organizations of any industry to achieve live actions with the help of SQLstream Blaze. SQLstream also works on most data sources such as Actian Ingres and ZeroMQ. This program works like the core of the system that collects, analyze and integrate to manage applications and operations as well.When it comes to providing the best services to the customers, SQLstream can dramatically increase customer service experience, better operations as well as automated services. Acquiring information is the first step to ensure that…

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Blaze is designed and patented as a distributed platform based on open standards and APIs for flexible development and deployment of scalable stream processing, reusable analytic operations, and applications.

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10

Oracle Stream Analytics

Oracle Stream Analytics is a powerful tool that helps businesses gain the right information or data from various sources that are beneficial to the organization. Its data streaming provides real time data insights that are crucial when making decisions within the business that would affect current and future connections with leads. Oracle Stream Analytics empowers users in organizations from any form of industry to create and implement fast data solutions in real time and instant insight encompassing SOA infrastructures, Big Data and the Internet of Things IoT. Oracle Stream Analytics enables fast data that requires extracting the value from highly…

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The main features of the Oracle Stream Analytics include Visual GEOProcessing with GEOFence relationship Spatial analytics and New Expressive Patterns Library, including Spatial, Statistical, General industry and Anomaly detection, streaming machine learning.

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11

IBM Streams

IBM Streams provides an advanced analytics platform that aims to help businesses to manage their user developed applications to better analyze, ingest and compare information from different sources. With so many data that a particular organization may have, having a trusted advance analytic program will enhance their day to day system management. The IBM Streams’ advanced platform can handle bigger amount of data and even millions of events or messages per second and can still provide the right solution for queries. Tools that are used with IBM Streams can forecast future events and provides the company of these behaviors and…

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Includes toolkits and accelerators for advanced analytics, including a telco event data accelerator that analyzes large volumes of streaming data from telecommunications systems in near real time and a social data accelerator for analyzing social media data.

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12

SAP Event Stream Processor

SAP Event Stream Processor is an event processing platform that helps businesses capture, analyze and get real time event streams to ensure a company’s better data management. By using the Internet of Things (IoT) as a source, and becoming responsive and quick on actions, a particular company will have a better understanding on how to effectively relate to customers and be productive for better outputs.SAP Event Stream Processor helps a company be informed of new information and provide a continuous act on it. By monitoring real time data as well as possible threats, a company will be able to respond…

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SAP Event Processor monitor incoming event streams for trends, patterns, and
correlations – and respond in real time and use alerts and push notifications to notify users of emerging opportunities or threats.

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13

Azure Stream Analytics

Azure Stream Analytics helps to develop and deploy low-cost solutions to gain real-time insights from devices, sensors, infrastructure, and applications. Use it for Internet of Things (IoT) scenarios, such as real-time remote management and monitoring or gaining insights from devices like mobile phones and connected cars. Azure Stream Analytics uses familiar SQL based language for faster development. Azure Stream Analytics enables correlating across different or multiple data streams. Be able to stream millions of events per second fast. Processed events are always available real time while also comparing multiple streams with various historical information, values and models. Detecting frauds gives…

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Azure Stream Analytics uses familiar SQL based language for faster development. Azure Stream Analytics enables correlating across different or multiple data streams.

7.6
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Azure Stream Analytics

14

Informatica

Informatica provide solution that is optimized to collect both structured and unstructured stream and machine data directly into a high performance data warehousing appliances, including Hadoop as well as other analytic platforms. Accessing and integrating new data sources for maximum advantage to the company as well as allowing data streaming collection using LAN or WAN. Informatica also corrects, standardize and replicate information before they are loaded. Informatica allows users to redirect workloads for better performance as well. This program provides quality insights that are valuable for the business to ensure better data management as well as solution providing. Informatica’s big…

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Provides out-of-the-box, high-performance connectivity to all enterprise data, eliminating the risk and cost of hand coding.

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Informatica

15

StreamAnalytix

StreamAnalytix is created to deliver a better option for enterprises to help them manage huge amount of data used to ensure that they are always informed of their online presence as well as business management concerning their customer’s preferences and information. By integrating multiple engines in to a single platform and enterprise can focus more on other priorities and let StreamAnalytix do the job. Most open source application requires a lot of time starting from scratch while commercial products may offer expensive services to which StreamAnalytix was able to break and offer the best of both worlds.Real Time VOIP and…

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StreamAnalytix simplifies the trade-off by integrating multiple engines in a single platform so that you can focus on your business rather than worrying about the underlying technology.

7.5
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StreamAnalytix

16

TIBCO Event Processing

TIBCO Event Processing is created for businesses to help conquer challenges and seize opportunities and turn it into a complete advantage for their own. By augmenting a company’s traditional data intelligence, TIBCO Event Processing will be able to find an event-driven solution for better data management.By using data analysis, discover what actions are needed to be done in order to transform the company and be able to anticipate awareness on customer’s preferences and needs from the business. By getting the right information of the customer, a company will be able to act according to their needs. TIBCO Event Processing’s analytics…

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TIBCO’s Event Analytics solutions make it easier to interact with machines, collaborate, and act faster than ever before.

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