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                                                    Citus Data

                                                    Discussion of Citus Data and CitusDB

                                                    February 18, 2015

                                                    Greenplum is being open sourced

                                                    While I don’t find the Open Data Platform thing very significant, an associated piece of news seems cooler — Pivotal is open sourcing a bunch of software, with Greenplum as the crown jewel. Notes on that start:

                                                    Greenplum, let us recall, is a pretty decent MPP (Massively Parallel Processing) analytic RDBMS. Various aspects of it were oversold at various times, and I’ve never heard that they actually licked concurrency. But Greenplum has long had good SQL coverage and petabyte-scale deployments and a columnar option and some in-database analytics and so on; i.e., it’s legit. When somebody asks me about open source analytic RDBMS to consider, I expect Greenplum to consistently be on the short list.

                                                    Further, the low-cost alternatives for analytic RDBMS are adding up. Read more

                                                    November 30, 2014

                                                    Thoughts and notes, Thanksgiving weekend 2014

                                                    I’m taking a few weeks defocused from work, as a kind of grandpaternity leave. That said, the venue for my Dances of Infant Calming is a small-but-nice apartment in San Francisco, so a certain amount of thinking about tech industries is inevitable. I even found time last Tuesday to meet or speak with my clients at WibiData, MemSQL, Cloudera, Citus Data, and MongoDB. And thus:

                                                    1. I’ve been sloppy in my terminology around “geo-distribution”, in that I don’t always make it easy to distinguish between:

                                                    The latter case can be subdivided further depending on whether multiple copies of the data can accept first writes (aka active-active, multi-master, or multi-active), or whether there’s a clear single master for each part of the database.

                                                    What made me think of this was a phone call with MongoDB in which I learned that the limit on number of replicas had been raised from 12 to 50, to support the full-replication/latency-reduction use case.

                                                    2. Three years ago I posted about agile (predictive) analytics. One of the points was:

                                                    … if you change your offers, prices, ad placement, ad text, ad appearance, call center scripts, or anything else, you immediately gain new information that isn’t well-reflected in your previous models.

                                                    Subsequently I’ve been hearing more about predictive experimentation such as bandit testing. WibiData, whose views are influenced by a couple of Very Famous Department Store clients (one of which is Macy’s), thinks experimentation is quite important. And it could be argued that experimentation is one of the simplest and most direct ways to increase the value of your data.

                                                    3. I’d further say that a number of developments, trends or possibilities I’m seeing are or could be connected. These include agile and experimental predictive analytics in general, as noted in the previous point, along with:? Read more

                                                    July 23, 2014

                                                    Teradata bought Hadapt and Revelytix

                                                    My client Teradata bought my (former) clients Revelytix and Hadapt.* Obviously, I’m in confidentiality up to my eyeballs. That said — Teradata truly doesn’t know what it’s going to do with those acquisitions yet. Indeed, the acquisitions are too new for Teradata to have fully reviewed the code and so on, let alone made strategic decisions informed by that review. So while this is just a guess, I conjecture Teradata won’t say anything concrete until at least September, although I do expect some kind of stated direction in time for its October user conference.

                                                    *I love my business, but it does have one distressing aspect, namely the combination of subscription pricing and customer churn. When your customers transform really quickly, or even go out of existence, so sometimes does their reliance on you.

                                                    I’ve written extensively about Hadapt, but to review:

                                                    As for what Teradata should do with Hadapt: Read more

                                                    May 6, 2014

                                                    Notes and comments, May 6, 2014

                                                    After visiting California recently, I made a flurry of posts, several of which generated considerable discussion.

                                                    Here is a catch-all post to complete the set.? Read more

                                                    May 2, 2014

                                                    Introduction to CitusDB

                                                    One of my lesser-known clients is Citus Data, a largely Turkish company that is however headquartered in San Francisco. They make CitusDB, which puts a scale-out layer over a collection of fully-functional PostgreSQL nodes, much like Greenplum and Aster Data before it. However, in contrast to those and other Postgres-based analytic MPP (Massively Parallel Processing) DBMS:

                                                    *One benefit to this strategy, besides the usual elasticity and recovery stuff, is that while PostgreSQL may be single-core for any given query, a CitusDB query can use multiple cores by virtue of hitting multiple PostgreSQL tables on each node.

                                                    Citus has thrown a few things against the wall; for example, there are two versions of its product, one which involves HDFS (Hadoop Distributed File System) and one of which doesn’t. But I think Citus’ focus will be scale-out PostgreSQL for at least the medium-term future. Citus does have actual customers, and they weren’t all PostgreSQL users previously. Still, the main hope — at least until the product is more built-out — is that existing PostgreSQL users will find CitusDB easy to adopt, in technology and price alike.

                                                    Read more

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