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MySQL vs Oracle: core differences and similarities

Given an overwhelming variety of databases, choosing the best fit for your application is not a trivial task. Different aspects of your project have to be considered to find the database that perfectly matches its requirements. 

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Which Data Source to Choose to Boost Your Pivot’s Performance

Being designed to process and render large volumes of data, Flexmonster Pivot Table & Charts allows you to work with a dataset of any size in a fast and robust way. All companies from small businesses up to worldwide enterprises can benefit greatly from using Flexmonster. Our component easily renders 1 million unique rows, works with OLAP data cubes and Elasticsearch. These are the unique features that distinguish our component from the rest.

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Release highlights: improving UX of Flexmonster

With user-centered design in mind, we always strive to deliver top-notch UI updates to you.

But we care not only about making the design of the component visually appealing but also about ensuring that your interaction with Flexmonster is delightful and intuitive in all respects.

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Flexmonster Performance: A Million Rows in Seconds

You definitely have noticed how swiftly Flexmonster displays thousands and millions of rows of your data.

But have you ever wondered how the pivot table component renders the rows of cells so fast each time you load a large data file? 

Let’s shed some light on the reasons for fast performance and develop an understanding of how Flexmonster works. 

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NEW: Pivot Table for Kibana

Pivot Table for Kibana is ready and at your service.

Our latest release has been noted with a new feature that allows users to display data from Elasticsearch. We saw how swiftly it had been picked up by our customers and decided to enrich this feature even more.

We made a step ahead and created a pivot table plugin for Kibana users. Using a pivot table just like any other tool from the Kibana UI could greatly simplify the work with data. And we will show you how to.

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Mondrian vs Elasticsearch: What to Choose For Your Project

Finding an analytics back-end engine for your business application is a challenge for developers and data warehouse architects.

Your choice always depends on a wide range of business, application-specific and hardware requirements which need to be considered in the early phases of the software development lifecycle. (more…)

NEW! 2.7 Version. Look out for improvements

When you are a developer who is searching for a web tool as a part of your solution, what are your selection criteria?

Most likely your choice will fall on:

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NEW Pivot 2.7: Use extra filters for your reports

It goes without saying that filtering is one of the main pivot table features. By outlining a specific set of data it helps focus on what matters more.

Previously, with our component you were able to use three kinds of filtering: by members, by values and a report filter. (more…)

New Pivot 2.7: optimized for your browser’s memory

Only one release ago our development team made a massive reduction of browser’s memory consumption by our Pivot. This is a tangible optimization for all clients that extended the ability of our product to load more data.
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Introducing Flexmonster Pivot for Elasticsearch

Today we are glad to announce that we have released a public version of Flexmonster Pivot Table & Charts that supports Elasticsearch data source. To put it simply, from now you can create insightful reports based on the data from an Elasticsearch index directly in the browser. And, as always, Flexmonster requires minimum efforts to set up the configuration to do that. The whole process is truly time-saving. You can make it sure by personal experience.

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Showcase: Junar Delivers Open Data Platform with Online Reporting Enhanced by Flexmonster Pivot Component


Company Profile
Name: Junar
Region: United States
Industry: IT solutions
Function: Data Economy, Open Data, Big Data (more…)

Multidimensional vs Tabular SSAS models: we support both

When analyzing really large data sets, we use Microsoft SQL Server Analysis Services. OLAP cubes allow coping with much bigger data volumes than relational databases. However, lots of users claimed that multidimensional cubes were hard to understand, especially when designing the model.

That was one of the reasons why SSAS Tabular Model was introduced in 2012. (more…)