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      GIS and geospatial

      Analysis of data management technology optimized for geospatial data, whether by specialized indexing or user-defined functions

      June 25, 2018

      New legal limits on surveillance in the US

      The United States has new legal limits on electronic surveillance, both in one specific way and — more important — in prevailing judicial theory. This falls far short of the protections we ultimately need, but it’s a welcome development even so.

      The recent Supreme Court case Carpenter v. United States is a big deal. Let me start by saying:

      *The Katz test basically says that that an individual’s right to privacy is whatever society regards as a reasonable expectation of privacy at that time.

      **The third-party doctrine basically says that any information of yours given voluntarily to a third party isn’t private. This includes transactional information such as purchases or telephone call detail records (CDRs)

      Key specifics include: Read more

      December 18, 2016

      Introduction to Crate.io and CrateDB

      Crate.io and CrateDB basics include:

      In essence, CrateDB is an open source and less mature alternative to MemSQL. The opportunity for MemSQL and CrateDB alike exists in part because analytic RDBMS vendors didn’t close it off.

      CrateDB’s not-just-relational story starts:

      Read more

      May 20, 2015

      MemSQL 4.0

      I talked with my clients at MemSQL about the release of MemSQL 4.0. Let’s start with the reminders:

      The main new aspects of MemSQL 4.0 are:

      There’s also a new free MemSQL “Community Edition”. MemSQL hopes you’ll experiment with this but not use it in production. And MemSQL pricing is now wholly based on RAM usage, so the column store is quasi-free from a licensing standpoint is as well.

      Read more

      April 16, 2015

      Notes on indexes and index-like structures

      Indexes are central to database management.

      Perhaps it’s time for a round-up post on indexing. ??

      1. First, let’s review some basics. Classically:

      2. Further:? Read more

      April 17, 2014

      MongoDB is growing up

      I caught up with my clients at MongoDB to discuss the recent MongoDB 2.6, along with some new statements of direction. The biggest takeaway is that the MongoDB product, along with the associated MMS (MongoDB Management Service), is growing up. Aspects include:

      Read more

      September 3, 2013

      The Hemisphere program

      Another surveillance slide deck has emerged, as reported by the New York Times and other media outlets. This one is for the Hemisphere program, which apparently:

      Other notes include:

      I’ve never gotten a single consistent figure, but typical CDR size seems to be in the 100s of bytes range. So I conjecture that Project Hemisphere spawned one of the first petabyte-scale databases ever.

      Hemisphere Project unknowns start:? Read more

      August 24, 2013

      Hortonworks business notes

      Hortonworks did a business-oriented round of outreach, talking with at least Derrick Harris and me. Notes? from my call — for which Rob Bearden didn’t bother showing up — include, in no particular order:

      In Hortonworks’ view, Hadoop adopters typically start with a specific use case around a new type of data, such as clickstream, sensor, server log, geolocation, or social.? Read more

      April 25, 2013

      Analytic application themes

      I talk with a lot of companies, and repeatedly hear some of the same application themes. This post is my attempt to collect some of those ideas in one place.

      1. So far, the buzzword of the year is “real-time analytics”, generally with “operational” or “big data” included as well. I hear variants of that positioning from NewSQL vendors (e.g. MemSQL), NoSQL vendors (e.g. AeroSpike), BI stack vendors (e.g. Platfora), application-stack vendors (e.g. WibiData), log analysis vendors (led by Splunk), data management vendors (e.g. Cloudera), and of course the CEP industry.

      Yeah, yeah, I know — not all the named companies are in exactly the right market category. But that’s hard to avoid.

      Why this gold rush? On the demand side, there’s a real or imagined need for speed. On the supply side, I’d say:

      2. More generally, most of the applications I hear about are analytic, or have a strong analytic aspect. The three biggest areas — and these overlap — are:

      Also arising fairly frequently are:

      I’m hearing less about quality, defect tracking, and equipment maintenance than I used to, but those application areas have anyway been ebbing and flowing for decades.

      Read more

      February 21, 2013

      One database to rule them all?

      Perhaps the single toughest question in all database technology is: Which different purposes can a single data store serve well? — or to phrase it more technically — Which different usage patterns can a single data store support efficiently? Ted Codd was on multiple sides of that issue, first suggesting that relational DBMS could do everything and then averring they could not. Mike Stonebraker too has been on multiple sides, first introducing universal DBMS attempts with Postgres and Illustra/Informix, then more recently suggesting the world needs 9 or so kinds of database technology. As for me — well, I agreed with Mike both times. ??

      Since this is MUCH too big a subject for a single blog post, what I’ll do in this one is simply race through some background material. To a first approximation, this whole discussion is mainly about data layouts — but only if we interpret that concept broadly enough to comprise:

      To date, nobody has ever discovered a data layout that is efficient for all usage patterns. As a general rule, simpler data layouts are often faster to write, while fancier ones can boost query performance. Specific tradeoffs include, but hardly are limited to: Read more

      July 15, 2012

      Memory-centric data management when locality matters

      Ron Pressler of Parallel Universe/SpaceBase pinged me about a data grid product he was open sourcing, called Galaxy. The idea is that a distributed RAM grid will allocate data, not randomly or via consistent hashing, but rather via a locality-sensitive approach. Notes include:

      The whole thing is discussed in considerable detail in a blog post and a especially in a Hacker News comment thread. There’s also an error-riddled TechCrunch article. Read more

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