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Streaming Analytics Platforms - Further Information

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Cover for Software AG Apama and the Internet of Things

Software AG Apama and the Internet of Things

While this paper focuses on Software AG Apama it is not a review of Apama per se, but rather of Software AG’s approach to IoT Analytics.
The cover for StreamAnalytix

StreamAnalytix

This paper discusses and evaluates StreamAnalytix, an analytics platform for both real-time, streaming data and for batch processing.
Cover for the Kx Systems InBrief

Kx Systems

Kx technology supports the rapid analysis of time-series data and, more generally, the analysis of streaming, in-memory and historical data.
Cover for Streaming Analytics 2018

Streaming Analytics 2018

This Market Update considers both stream processing platforms upon which you might build analytics as well as streaming analytics platforms per se.
Cover for IBM Streams and Steaming Analytics

IBM Streams and Streaming Analytics

IBM Streams (previously IBM InfoSphere Streams) is a high performance, low latency platform for analysing and scoring data in real-time. It is a part of the IBM Watson & Cloud Platforms.
Cover for the Software AG Apama InBrief

Software AG Apama

Software AG’s Apama was first released in 2001 as a complex event processing platform targeted at supporting algorithmic trading in capital markets. It remains a market leader in that space though IoT now forms a major target market.
Cover for the SQLstream InBrief

SQLstream

SQLstream Blaze, which is the name for the SQLstream suite of products, is a streaming analytics platform that is available for both on-premises and cloud-based deployments. As it’s name suggests it is based on ANSI standard SQL.
Cover for the EsperTech InBrief

EsperTech

EsperTech is the company behind the open source Esper (Java based) and NEsper (.Net based) products, where the former was one of the first CEP engines to be introduced.
Cover for SAS Event Stream Processing

SAS Event Stream Processing

SAS has been offering stream processing for a number of years, especially for fraud applications. However, a major driver is now the Internet of Things (IoT) and applications such as predictive maintenance and smart “anything”.
Cover for TIBCO StreamBase

StreamBase

TIBCO StreamBase is the streaming analytics component of TIBCO’s ‘connected intelligence’ product collection, that allows businesses to better connect, understand and interact with their data.
Cover for the Striim InBrief

Striim

Striim is a streaming integration and analytics platform. Without de-emphasising the latter, it focuses on the former.
The cover of Streamlio (InBrief)

Streamlio

Founded in 2018, Streamlio provides an intelligent platform for handling (streaming) data in motion.
Cover for Streaming Analytics 2016

Streaming Analytics 2016

Streaming analytics enables businesses to respond appropriately and in real-time to context-aware insights delivered from fast data.
Cover for Streams, events and analytics

Streams, events and analytics

Stream processing is enjoying a resurgence thanks to big data and the emergence of the Internet of Things.
Cover for Ancelus

Ancelus

Ancelus is an ACID compliant database with extreme performance characteristics, developed and marketed by Time Compression Strategies Corporation (TCSC).
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Big data integration

The fourth issue for big data is integration, where agility will be required (as it is for governance)
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TIBCO transforms big data into big opportunity

TIBCO came to London for their user conference (transFORM2013). This year's theme was all about big data and TIBCO's senior executives outlined their strategy for their platform.
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CEP and Big Data 2

Should it be called CEP? Is CEP only about real-time BI? These were questions we answered 6 years ago. Also, a mention of some Hadoop-based CEP engines.
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Simplifying CEP

The C in CEP may stand for "complex" but CEP itself is not complex
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Untangling events part 3

There has been some delay in this, the third and final article on untangling events. And just as well. I initially asked the question as to whether the log and event management vendors were more...
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Untangling events part 2

The purpose of this series of articles is to identify if all of the different approaches to handling events are part of a single market or whether they should be treated as separate. In the first...
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Applying data warehousing principles to event processing

It is now pretty much agreed that in data warehousing environments you need a massively parallel processing (MPP) architecture in order to handle very large data volumes. The important factor is...
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Untangling events part 1

Complex event processing, business event processing, security event management, log management, data retention systems, event-driven architecture, event warehousing: are these topics and other...
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IBM events: not the whole story

A couple of months ago I reported on the announcement of IBM InfoSphere Streams as the company's high end (complex) event processing platform. I also described IBM's approach to event processing...
Cover for (Complex) Event Processing

(Complex) Event Processing

This paper seeks to explain what events are, why they are important to your business, and what the options are for processing and managing these events.
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Event processing moving forward

A discussion of some the various ways in which the event processing market is moving forward.
Cover for Event Processing

Event Processing

This report describes the technology and what it is good for, including providing a series of use cases. In other words: what event processing is, how it works and where you might use it.
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Real-time data warehousing – a change in the air?

Will the current approach to real-time data warehousing be replaced with a combination of event processing engines and data warehouse appliances?
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The difference between complex event processing and event stream processing

There is a difference between ESP and CEP and between CEP and business process modelling or rules engines: AptSoft provides a good example.
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