Posts Tagged ‘SaffronSierra’

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SaffronSierra & Gmail Classification

Friday, April 30th, 2010 by Jared Peterson

I’ve recently added some sample code to our “examples” repository that demonstrates how to use SaffronMemoryBase running on SaffronSierra to do basic email classification. The example leverages the convenience of labels within Gmail to provide the “labels” for classifying future emails.

If you have a Gmail account (or a Google Apps account) then you already know that as emails come in you can associate them with labels. You might have labels such as “accounts”, “soccer”, “music”, “work”, etc… (those are some of mine anyway). As I started thinking about building an email classification example it occurred to me that the labels within Gmail would provide a nice, easy way of doing classification. By “labeling” emails in Gmail I’ve already made the statement, “This email is about work”, or “This email is about soccer”. Why not leverage that hard work?

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SaffronSierra Refresh

Friday, April 16th, 2010 by Jared Peterson

We just pushed out a minor refresh to SaffronSierra. As a user you won’t notice much that’s different (hopefully). This refresh brings with it a couple of changes. One that users will see, and another they won’t. Let me talk about both briefly:

  • Nightly Running Reminders – SaffronSierra is a pay-as-you-go service. You pay for every hour your service is running. SaffronSierra makes it really simple (you click a button) to start a SaffronMemoryBase system. It’s so simple in fact that it’s easy to start it and forget that it’s running. Now SaffronSierra will send email reminders every night to users who’s SaffronSierra service is running. If you actually want your service to be running 24/7 (which is totally fine by the way), and you don’t want to receive these reminders you can login and update your user profile.
  • New Amazon AWS Java Libraries – SaffronSierra uses Amazon AWS as it’s backend infrastructure for running services. The java library we originally used to integrate with AWS has been deprecated. So, we ported SaffronSierra over to the new java library. This actually was a pretty painless process. There are some differences between the two libraries, but as I told someone recently “it’s different in the ways that it needs to be different.” Hopefully you won’t notice this change and things just keep humming along.

We’ll keep the updates coming, stay tuned.

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TweetDive Source Code

Wednesday, April 14th, 2010 by Jared Peterson

I’m happy to announce that we’ve made the TweetDive source code publicly available (finally). I know a number of people have been waiting to get their hands on it. For details on how to grab it from Subversion take a look at this page.

We hope this code will provide a quick-start for developers getting started with SaffronSierra. TweetDive uses a number of different REST APIs available on SaffronSierra. You can use it as a reference as you build your own stuff, or you can extend TweetDive with new features. If you’d like to see your changes incorporated into the running version of TweetDive please contact us. We’d be happy to incorporate patches.

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Updated Pricing

Wednesday, April 7th, 2010 by Jared Peterson

Starting today we’ve changed the way pricing works for SaffronSierra. Hopefully you will find our new approach much simpler. What is our new approach? Some would  call it “pay-as-you-go”. Quite simply there is a per-hour rate based on what type of SaffronSierra cluster you’re running. The per-hour rate starts at $1.00 an hour and goes up from there. There is no commitment, we just bill you every month for the time you use. If you haven’t used your service then you won’t be billed. Pretty simple right?

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The Big Red Easy Button

Tuesday, March 30th, 2010 by Jim Fleming

Better known as SaffronSierra.  Today Saffron announced the availability of SaffronSierra, a cloud delivery of the SaffronMemoryBase platform.  As you know, SaffronSierra allows developers a quick and easy way to provision an associative memory “data service” with a push of a button.  How easy is that?  SaffronSierra will soon become even easier with a “no commitment, charge by the hour” payment plan, as well as, the ability to scale your service up to handle very large data volumes.  If you are curious about the associations you might find in your data, now is a good time to try SaffronSierra, you have nothing to lose.

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REST API Announcement

Tuesday, March 23rd, 2010 by Jim Fleming

Today Saffron announced our REST APIs for sense-making and decision support applications using SaffronMemoryBase (SMB).  With these REST APIs, we’ve taken an otherwise difficult subject and made it easy.  Similar to how REST has simplified SOA, Saffron’s REST APIs have simplified analytics.  Notable features of our API are:

  1. Powerful, yet simple to use.  For example, to ask what products are connected to the company saffron in the context of announcement, would be as easy as HTTP GET: http://hostname/ws/spaces/default/connections?q=saffron,announcement&c=product
  2. Includes both administration and application APIs.
  3. Includes both ingestion (write) and query (read) APIs.
  4. Queries cover everything from low-level (e.g. returning a sub-matrix of association counts) to high-level (e.g. returning rank-ordered list of association trends) operations.
  5. The API is not overwhelming.  There are a small number of APIs that can be applied different ways to solve many problems.
  6. Dynamically combine associations together in various ways at query time.  SMB’s virtual attribute system even allows the system to “see” multiple attributes as one, providing a way to fix-up data cleansing errors (e.g. Bill and William are really the same person).
  7. Standard JSON/XML input/output formats.
  8. SMB’s performance and REST API is ideally suited for today’s new class of analytical applications.

For more information about Saffron REST APIs please visit SaffronSierraSaffron Technology or view today’s news announcement.

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What is SaffronSierra (in plain english)?

Wednesday, February 17th, 2010 by Jared Peterson

I recently received a request to describe SaffronSierra “in plain english”, this post will attempt to do just that.

SaffronSierra is a cloud-based, hosted version of SaffronMemoryBase. SaffronSierra enables developers to easily leverage the analytical powers of SaffronMemoryBase using a simple REST API. Using SaffronSierra, you don’t have to worry about downloading, installing and configuring software. You simply login to your SaffronSierra console and press “Start”. Within minutes, you will have a private instance of SaffronSierra ready for your use. Once your service is available you can start putting your data into SaffronSierra and powering your applications with advanced analytics. We hope that SaffronSierra enables people to quickly realize the benefits of SaffronMemoryBase in a low-cost, low-risk way.

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TweetDive Worlds

Tuesday, February 16th, 2010 by Jared Peterson

Up until today if you were to login into TweetDive you would have only seen data from what we call the “Money” world. TweetDive could only display Twitter data that had been ingested into this one SaffronSierra instance. Today we refreshed TweetDive and now users have access to more “worlds”. A “world” represents a Twitter account paired with a SaffronSierra instance. Now when you login you should see the world selector towards the top-right of the screen.

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TweetDive Introduction (Part 1)

Monday, February 8th, 2010 by Jared Peterson

This is a screencast that I put together that covers some of the basics of using TweetDive.

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Observing & Querying Tweets (Part 3)

Wednesday, January 13th, 2010 by Jared Peterson

In my previous posts I’ve discussed how to fetch data from Twitter and massage it into the form that is needed when observing data in Sierra. I also talked about how to “POST” that data to Sierra so that it’s available to query. In this post I’m going to discuss the process of actually querying that data once it’s in Sierra.

Before you read on you may want to browse over the Sierra documentation. These docs list all of the REST calls that are available on Sierra. In my example below I’ll be using the “connections” call.

I should also note that I’ve made some additions to the source code that I’ve used across all of these posts. That code is available along with the rest of the Sierra sample code. In particular I’ve made the code aware of command-line options that specify whether you are “observing” (-o) or “querying” (-q). You can also define all of the needed usernames and passwords via the command-line as well.

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