Podcast Recording Shootout
The two main contenders that are suitable for workhorse podcast use are Skype and Gizmo. Both are very easy to download and install. Both offer comparable rates on calls coming in from the phone network and going out again, both nationally and internationally (though Gizmo has a slight edge in this respect). Both are user-friendly and easy to get potential guests set up on so they can be on your show.
They both are usable. They both are workable. They both run quite well on Linux, Windows and Mac OS. Their feature sets are comparable in many respects. But, they are not the same.
Whither 64?
Neither Skype nor Gizmo offers anything in the way of 64-bit versions for Linux, even though there are user complaints and pleadings about this dating back to May 2005 on both companies' support forums on exactly this topic. Skype recently has introduced a 64-bit Vista client, but Mac and Linux 64-bit clients are, as yet, nothing more than a pleasant adolescent fantasy for the lonely off-platform user. Gizmo, meanwhile, is 32-bits all through.
Both install and run on 64-bit distros, with a little bit of a headache making sure they've got the right 32-bit libs to call in and with setting up the chroot environment. It's a stopgap that works okay, but it ain't pretty, and in a time when 32-bit desktop and laptop processors are being end-of-lifed by hardware manufacturers, this situation really is irritating.
Skype, now the prized stepchild of the eBay corporation, runs on a proprietary peer-to-peer networking back end that co-opts the user's system resources to route calls, up to the maximum of what it can grab that's not being used by other systems. This is comparable to how BitTorrent works, though unlike with BitTorrent, users have no control over how much in the way of bandwidth or system resources they want to allocate to the task. The practical upshot for this where performance is concerned is curiously double-edged. At the beginning of a Skype call, the connection typically is loud and clear, the mix is well proportioned, and the compression artifacts are very difficult to hear (and, if you're good with EQs, you can pretty much notch out the most obvious ones). However, as a call progresses, more of your personal bandwidth gets allocated to other network calls, and the quality of the audio gradually degrades. At low traffic times, this effect is barely noticeable, but at high traffic times, you may find yourself having to restart the call every 10–15 minutes as the quality falls below what you find acceptable (or intelligible).
Its networking setup isn't the only thing that's proprietary—it's also a closed system. Skype's network can't be dialed in to directly from any other voice-conferencing network. The standards are closed, and they're black-boxed. Although this isn't a problem that's directly relevant to podcasting, if you're looking for a general first-line VoIP package, it's something you'll want to keep in mind. Skype is like Vegas: what happens there, stays there—well, assuming its encryption algorithms are robust.
Gizmo, a service and application owned by SIPphone, Inc., has a somewhat different approach. Although the software itself is proprietary, it uses the open SIP protocol for its transport across the Net, and calls are routed directly over the SIPphone network between the individual call participants, rather than being routed through a peer-to-peer network. Because it uses SIP and Jabber, it can hook up with any software using either of these protocols fairly transparently.
Gizmo uses TLS and SSL encryption to discourage eavesdropping—open technologies whose strengths and limitations are well known. The corporate culture is deliberately geared toward transparency rather than toward opacity, which is an operating philosophy that warms the cockles of this Linux geek's heart. However, when it comes to encryption, Gizmo also loses a point, as it does not encrypt between Gizmo and non-Gizmo SIP clients.
The sound quality on Gizmo follows a different curve from Skype. Because Gizmo routes over the SIP network instead of through a peer-to-peer setup, it is more subject to the fickle winds of fate. When Net traffic is up, Gizmo calls tend to decay. When it's down, they do better. However, Gizmo does not progressively degrade performance over the course of a call or take your bandwidth for allocating to other calls on the network.
In terms of actual performance, the sound quality is usually a wash, but Gizmo consistently sounded better the times I've used it for multiparty conferences than has Skype, particularly on extra long calls.
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Sponsored by AMD
If you already use virtualized infrastructure, you are well on your way to leveraging the power of the cloud. Virtualization offers the promise of limitless resources, but how do you manage that scalability when your DevOps team doesn’t scale? In today’s hypercompetitive markets, fast results can make a difference between leading the pack vs. obsolescence. Organizations need more benefits from cloud computing than just raw resources. They need agility, flexibility, convenience, ROI, and control.
Stackato private Platform-as-a-Service technology from ActiveState extends your private cloud infrastructure by creating a private PaaS to provide on-demand availability, flexibility, control, and ultimately, faster time-to-market for your enterprise.
Sponsored by ActiveState
| Non-Linux FOSS: libnotify, OS X Style | Jun 18, 2013 |
| Containers—Not Virtual Machines—Are the Future Cloud | Jun 17, 2013 |
| Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer | Jun 12, 2013 |
| Weechat, Irssi's Little Brother | Jun 11, 2013 |
| One Tail Just Isn't Enough | Jun 07, 2013 |
| Introduction to MapReduce with Hadoop on Linux | Jun 05, 2013 |
- Containers—Not Virtual Machines—Are the Future Cloud
- Non-Linux FOSS: libnotify, OS X Style
- Linux Systems Administrator
- Validate an E-Mail Address with PHP, the Right Way
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Senior Perl Developer
- Technical Support Rep
- UX Designer
- Introduction to MapReduce with Hadoop on Linux
- RSS Feeds
Featured Jobs
| Linux Systems Administrator | Houston and Austin, Texas | Host Gator |
| Senior Perl Developer | Austin, Texas | Host Gator |
| Technical Support Rep | Houston and Austin, Texas | Host Gator |
| UX Designer | Austin, Texas | Host Gator |
| Web & UI Developer (JavaScript & j Query) | Austin, Texas | Host Gator |
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?




1 hour 44 min ago
2 hours 10 min ago
4 hours 38 min ago
5 hours 12 min ago
5 hours 12 min ago
5 hours 13 min ago
5 hours 15 min ago
5 hours 17 min ago
5 hours 18 min ago
5 hours 19 min ago