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                                                    NoSQL

                                                    Discussion of NoSQL concepts, products, and vendors.

                                                    August 22, 2017

                                                    Imanis Data

                                                    I talked recently with the folks at Imanis Data. For starters:

                                                    Read more

                                                    June 30, 2017

                                                    Analytics on the edge?

                                                    There’s a theory going around to the effect that:

                                                    There’s enough truth to all that to make it worth discussing. But the strong forms of the claims seem overblown.

                                                    1. This story doesn’t even make sense except for certain new classes of application. Traditional business applications run all over the world, in dedicated or SaaSy modes as the case may be. E-commerce is huge. So is content delivery. Architectures for all those things will continue to evolve, but what we have now basically works.

                                                    2. When it comes to real-world appliances, this story is partially accurate. An automobile is a rolling network of custom Linux systems, each running hand-crafted real-time apps, a few of which also have minor requirements for remote connectivity. That’s OK as far as it goes, but there could be better support for real-time operational analytics. If something as flexible as Spark were capable of unattended operation, I think many engineers of real-world appliances would find great ways to use it.

                                                    3. There’s a case to be made for something better yet. I think the argument is premature, but it’s worth at least a little consideration.? Read more

                                                    June 16, 2017

                                                    Generally available Kudu

                                                    I talked with Cloudera about Kudu in early May. Besides giving me a lot of information about Kudu, Cloudera also helped confirm some trends I’m seeing elsewhere, including:

                                                    Now let’s talk about Kudu itself. As I discussed at length in September 2015, Kudu is:

                                                    Kudu’s adoption and roll-out story starts: Read more

                                                    March 12, 2017

                                                    Introduction to SequoiaDB and SequoiaCM

                                                    For starters, let me say:

                                                    Also:

                                                    Unfortunately, SequoiaDB has not captured a lot of detailed information about unpaid open source production usage.

                                                    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

                                                    November 23, 2016

                                                    DBAs of the future

                                                    After a July visit to DataStax, I wrote

                                                    The idea that NoSQL does away with DBAs (DataBase Administrators) is common. It also turns out to be wrong. DBAs basically do two things.

                                                    • Handle the database design part of application development. In NoSQL environments, this part of the job is indeed largely refactored away. More precisely, it is integrated into the general app developer/architect role.
                                                    • Manage production databases. This part of the DBA job is, if anything, a bigger deal in the NoSQL world than in more mature and automated relational environments. It’s likely to be called part of “devops” rather than “DBA”, but by whatever name it’s very much a thing.

                                                    That turns out to understate the core point, which is that DBAs still matter in non-RDBMS environments. Specifically, it’s too narrow in two ways.

                                                    My wake-up call for that latter bit was a recent MongoDB 3.4 briefing. MongoDB certainly has various efforts in administrative tools, which I won’t recapitulate here. But to my surprise, MongoDB also found a role for something resembling relational database design. The idea is simple: A database administrator defines a view against a MongoDB database, where views: Read more

                                                    November 23, 2016

                                                    MongoDB 3.4 and “multimodel” query

                                                    “Multimodel” database management is a hot new concept these days, notwithstanding that it’s been around since at least the 1990s. My clients at MongoDB of course had to join the train as well, but they’ve taken a clear and interesting stance:

                                                    When I pointed out that it would make sense to call this “multimodel query” — because the storage isn’t “multimodel” at all — they quickly agreed.

                                                    To be clear: While there are multiple ways to read data in MongoDB, there’s still only one way to write it. Letting that sink in helps clear up confusion as to what about MongoDB is or isn’t “multimodel”. To spell that out a bit further: Read more

                                                    October 3, 2016

                                                    Notes on the transition to the cloud

                                                    1. The cloud is super-hot. Duh. And so, like any hot buzzword, “cloud” means different things to different marketers. Four of the biggest things that have been called “cloud” are:

                                                    Further, there’s always the idea of hybrid cloud, in which a vendor peddles private cloud systems (usually appliances) running similar technology stacks to what they run in their proprietary public clouds. A number of vendors have backed away from such stories, but a few are still pushing it, including Oracle and Microsoft.

                                                    This is a good example of Monash’s Laws of Commercial Semantics.

                                                    2. Due to economies of scale, only a few companies should operate their own data centers, aka true on-prem(ises). The rest should use some combination of colo, SaaS, and public cloud.

                                                    This fact now seems to be widely understood.

                                                    Read more

                                                    September 6, 2016

                                                    “Real-time” is getting real

                                                    I’ve been an analyst for 35 years, and debates about “real-time” technology have run through my whole career. Some of those debates are by now pretty much settled. In particular:

                                                    A big issue that does remain open is: How fresh does data need to be? My preferred summary answer is: As fresh as is needed to support the best decision-making. I think that formulation starts with several advantages:

                                                    Straightforward applications of this principle include: Read more

                                                    August 7, 2016

                                                    Notes on DataStax and Cassandra

                                                    I visited DataStax on my recent trip. That was a tipping point leading to my recent discussions of NoSQL DBAs and misplaced fear of vendor lock-in. But of course I also learned some things about DataStax and Cassandra themselves.

                                                    On the customer side:

                                                    Customers in large numbers want cloud capabilities, as a potential future if not a current need.

                                                    One customer example was a large retailer, who in the past was awful at providing accurate inventory information online, but now uses Cassandra for that. DataStax brags that its queries come back in 20 milliseconds, but that strikes me as a bit beside the point; what really matters is that data accuracy has gone from “batch” to some version of real-time. Also, Microsoft is a DataStax customer, using Cassandra (and Spark) for the Office 365 backend, or at least for the associated analytics.

                                                    Per Patrick McFadin, the four biggest things in DataStax Enterprise 5 are: Read more

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