50 Open Source Replacements for Really Expensive Software

Posted on by Teddy Nee

The “Great Recession” has businesses and consumers alike looking for ways to cut costs. That includes looking for cheaper alternatives to expensive software.

Accounting: TurboCASH, Phreebooks

Business Intelligence: Jaspersoft, Pentaho, Palo BI Suite, JMagallanes, OpenReports

Business Process Management: ProcessMaker

CAD: BRL-CAD, Archimedes

Customer Relationship Management: Sugar Community Edition

Database: MySQL, Firebird, Kexi

Desktop Publishing: Scribus

E-mail/Collaboration/Groupware:  Zimbra

Enterprise Resource Planning (ERP): OpenERP, Openbravo, ADempiere

Gateway Security Appliances: Endian Firewall Community, Untangle

Graphics/Drawing: Dia, Gimp, Inkscape, Paint.Net

Office Productivity: OpenOffice.org, KOffice, NeoOffice, Oracle OpenOffice

Operating System: Red Hat, SUSE, Ubuntu, Debian

PDF Tools: PDFCreator

Point of Sale: Openbravo POS, Lemon POS

Project Management: OpenProj, GanttProject

Speech Recognition: Simon

Video Tools: Blender, Cinelerra, OpenShot Video Editor, Kdenlive, CineFX, Avidemux

Web Application Tools:  Open BlueDragon

Web Site Authoring: Kompozer, NVU, Bluefish, SeaMonkey

If you have any question or opinion, feel free to send us a messageor leave your comments below

Reference: 50 Open Source Replacements for Really Expensive Software

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Leverage cloud financial intelligence systems with AWS

Posted on by Teddy Nee

Leverage cloud financial intelligence systems with AWS

The use of cloud financial intelligence systems, typically from cloud financial management system providers, offers insights into cloud usage. Cloud financial management providers, such as Cloud Cruiser and others, can tell you how effective the cloud platforms are in delivery of services. This includes how each service tracks back to cloud resources that support the services, as well as who is consuming the services and by how much.

However, the true value of these systems is not the simple operational cost data that they are able to gather and report on — it’s the ability to leverage deeper analytics to determine usage patterns, and how those patterns will behave over time. This means you have the ability to better understand how your AWS instances (and other cloud services) were put to use in the past, and more importantly, how they will be leveraged in the future, including the ability to properly estimate cloud resource utilization in the context of complex and widely distributed architectures.

It’s all about the ability to make the most out of data from multiple components of the architecture, not just AWS. Most enterprises that deploy cloud-based systems do so using either public and private clouds within a multi-cloud architecture, which may also be mixed with traditional (or legacy) systems. This makes the financial tracking much more complex, but also much more valuable.

For example, a production management system may leverage core storage services from AWS, session management services from their OpenStack private cloud and core database services using a traditional Oracle database running in their data center. Thus, the cloud financial management system needs to gather information for many different system components, including the private and public clouds , as well as the local database. System owners can use this information to determine the amount of resources consumed, as well as patterns of consumption over time. They have a complete picture as to how a holistic system is functioning, including cloud and non-cloud components.

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Is ETL Development doomed?

Posted on by Teddy Nee

Is ETL Development doomed?

There seems to be a couple of tracks for this. First is the pure development automation tools, such as Varigence MIST. If you are technically minded, take a look at this product demo video – though I suggest skipping to about 25 minutes in to see the real meat as it does go on a bit. It looks mindbogglingly powerful but is clearly shooting at the ETL pro who wants to churn stuff out faster, more consistently and with less fiddling about. MIST is limited to SSIS/AS (for now) and I’m not sure how far it will go as it’s clearly aimed at the developer pro market, which is not always the big buyers. I expect to be playing with it more over the next few weeks on a live project so should be able to get a better view.

The second path appears to be more targeted at eliminating ETL developers in their entirety. AnalytixDS wraps up metadata import (i.e. you suck in your source and target metadata from the systems or ERWIN), do the mapping of fields and apply rules, then “push button make code”. Obviously there’s a bit more to it than that, but the less you care about your back end and the quality of your ETL code (cough Wherescape cough) the more likely this product will appeal to you. Say hello, business users, who are the big buyers (though I look forward to troubleshooting your non-scalable disasters in the near future).

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