Where I work, SQL Server 2008 is one of the databases that we will continue to support for the foreseeable future, as it is still very popular with our enterprise customers.
Microsoft SQL Server 2008 hold-outs took their first, tentative steps into an unsupported future today as the Windows giant finally pulled the plug on support for the venerable relational database. Come, hold hands, bid a fond farewell to an old friend, and sing songs of T-SQL, encryption and a seemingly never-ending …
Yeah nice... they're going to continue to come out with security updates but not make them available to their customers (unless they move to Azure).
Of course, if you move your current workload to Azure, you'll get these 3 years of free security udpates... at which point, they'll probably say you cannot run SQL Server 2008 on there AT ALL, and you'll have to move your workload BACK onto your own systems (which are then missing those 3 years of patches.) I mean, they're assuming you will by then have updated your stuff to work with newer SQL Server, then decide to keep it in Azure...
I was at an event run by Ed Baker about Server 2019 migration earlier this year. The Shift to Azure thing also applies to Server 2008/20008 R2. MS's plan does give you 3 years to work out how to shift legacy systems to newer infrastructure.
So, AFAIAA, the assumption is also partly that you could figure out how to keep it on site.
It's not tricky to see why it's much easier for Microsoft to continue to develop patches for SQL 2008 in Azure, where they have a single environment that's fully under their control. As opposed to writing and testing patches that have to work on XP, Vista, 2003, 2008 and 2008 R2, on both x86 and 64 bit systems (and Itanium).
(In a similar way that it's much easier for Apple to write OSX when they control all the hardware it will run on, compared to Windows which is expected to run on basically anything x86).
Yes of course this is a money grab, they're a for-profit company, what else are you expecting? However there are sound engineering reasons behind it.
SQL database is not a database everybody want! At all! And certainly not a relational database everybody seek for! Indeed, all records in SQL are pre-prepared, i.e. sorted manually, the uniqueness is absent, relations between entries are established manually. Isn't that a shame? I smell sulfur... the darkest middle ages...
AI relational blockchain database is radically different! Everything is done automatically, all records are automatically annotated with texts, the blockchain hierarchy is automatically built and all records are automatically sorted. For example, all text entries are automatically annotated with dictionary definitions (which makes them all absolutely unique), and numbers, symbols, images are annotated with text. Isn't that the miracle you so long were waited for? You may order one right now!
Ilya, you've been touting this line around various forums for years now. I remember you claiming that Amazon, Google, Ebay, Oracle, etc, were obsolete and will soon be out of business years ago. Why don't you build this excellent product that you keep eulogising about, and then see who comes knocking to make you rich beyond the dreams of avarice?
A suit somewhere in a boardroom would probably believe I.Geller too. The suit would be suckered right in and then lumber the IT team with the problem.
If it's just a database you want and you are with a clean sheet, no legacy, then you probably don't want SQL Server because Postgres or something will do most jobs well enough without costing you any money or committing you to a platform (yes I know there is a linux SQL Server RDBMS).
It's all the non RDBMS add ons and extra bits adorning SQL Server that sustain it in the market.
Listen! This whole AI story has its roots in the replacing n-gram parsing with AI-parsing. There is a sentence:
- Alice and Bob like strawberries.
N-gram parsing delivers only one phrase:
-- Alice and Bob like strawberries.
AI parsing gets two phrases:
-- Alice likes strawberries.
-- Bob likes strawberries.
That's the only difference between SQL and Artificial Intelligence technologies. Nothing else.
Get your snake-oil here!
Seriously - I'm no particular fan of one database engine over another, although I do use SQL Server every day, and my employer has been "good" enough to put me through the MS exams on it. This puts me in the position where I am aboslutely qualified to say that literally everything you just wrote is 100% guaranteed horseshit. I mean, you start off by essentially claiming that one of the world's best known RDBMSs isn't an RDBMS. You're not a flat-Earther are you?
You're right. But look at https://db-engines.com/en/ranking and see how many people do want them.
I began with Oracle over 20 years back, learned about DB2 shortly after and preferred that as doing >80% of what Oracle does for <20% of the effort. SQL Server 2008 was the first edition from MS that made me think it could handle enterprise applications, again doing most of what DB2 does with a lot less effort. Count the number of DBA's per database for each platform if you disagree.
There is another database though: Cambridge Semantics' AnzoGraph DB.
Its basic RDF model consists of the subject-predicate-object triple. So, if there is a triple "Alice loves champagne" AnzoGraph DB does not see these patterns:
- Alice loves
- Champagne is loved
I, however, patented subject-predicate-object triple for AI database, as well as all other kinds of doubles, triples, quadruples, etc.
That is AnzoGraph DB is not a databases since it loses information and cannot be trusted. However my patented AI databases lose nothing and is completely trustworthy. Plus my finds information in its context and subtexts, while AnzoGraph DB cannot ("That means that we have no way to identify the origin of a particular triple or record when it was asserted. Adding triples into a triple store loses context that is useful for many applications" https://www.cambridgesemantics.com/blog/semantic-university/semantic-web-design-patters/semantic-search-semantic-web-2-2/).
If your database architecture is so great, why are you shilling it here? Build something useful with it and blow away the competition. That's how you can make a name for it.
There are hundreds of industries that rely on databases. Here's an under-served market you can have right now: strata billing. People who buy commodities in bulk, then retail them to a niche or captive market. E.g., an apartment building owner billing their own tenants for electricity and water. There are tens of thousands of buildings like that in the world, and right now most of them are doing their billing in Excel.
I just told you how to make money. If you can't do it, then we will draw appropriate conclusions about your technology.
If you simply choose not to do it, that's another matter. I sympathise, I'm a lazy bastard myself. But then we'll draw another set of conclusions about your technology.
Yes, I have a finished product. But now I have to prove the validity of it. To do this I need a serious test. Have you an idea how much it will cost structuring of, for example, Patent Database of the United States? I know, that's why I sit tight hoping somebody would come and risk a small fortune. Structuring is actually quite expensive pleasure.
"now I have to prove the validity of it"
I don't think that you'll be able to get speculative investment unless you at least have a valid proof-of-concept.
It's hard to know what you have, though. Your comments are describing an approach that's been around for at least a couple of decades, so I assume that there's more to it than you've stated here.
What exists and is called "AI" is worthless until a trustworthy Patent Search (based on this AI concept) is created. Only it's the litmus paper, the fact that can confirm or deny the validity of this AI mechanism.
Do not forget that the AI answers questions? And that a Patent Search will allow the most objective assessment of the quality of this AI? The US patent Database is the most researched, the most extensive and accurate database on the planet.
Without this test SQL remains the only reliable method for storing and searching information.
Yes, I do claim that.
There is a sentence "Alice and Bob walk".
N-gram parsing produce only one phrase
- Alice and Bob walk.
"In the fields of computational linguistics and probability, an n-gram is a CONTINUOUS sequence of N items from a given sample of text or speech".
My AI-parsing produces three phrases here:
-- Alice walks
-- Bob walks
-- Alice and Bob walk.
Thus my AI database technology includes SQL n-gram parsing and adds a new fixture.
He'll be claiming that his DB bends spoons next... :) :)
In that case, would not his name be U Geller??
You've got it twisted:
He'll be claiming that his DB straightens spoons - bent by his more famous relation - hence the 'I'.
[Aside: Interestingly, if I remember my topology 'U' and 'I' are just variations of the same basic line shape.]
You are right. Sometimes I want to do something crazy, like Jura... For example, to write about noun-pronoun phrases. Is it quite in his spirit?
I said: "A contextual phrase is a 'predicative definition' characterized by combinations of nouns and other parts of speech such as the verb and adjective (e.g. city-be-in)." For example, a paragraph about the same idle Alice and Bob:
- Alice and Bob are coming. She enjoys to walk.
- Alice is coming - 0.25
- Bob is coming - 0.25
- Alice and Bob are coming - 0.5
- Alice enjoys - 0.25
- Alice walk - 0.25
- Alice enjoys to walk - 0.5
- she enjoys to walk - 0.5
- she enjoys - 0.25
- she walks - 0.25.
- she enjoys to walk -0.25
The numbers-weights (statistics) indicate the phrases importance - the more weight the more important the phrase. (This is my Differential Linguistics.)
There is a nouns-names phrase here ("Alice and Bob are coming"), its relatively higher weight (0.5) emphasize its greater importance.
I strongly believe Microsoft used this strategy structuring the sentence “The city councilmen refused the demonstrators a permit because they [feared/advocated] violence.” This sentence is a part of a paragraph or is surrounded by paragraphs, which have their own synonymous clusters about the city councilmen and the demonstrators. From them Microsoft can conclude what is going on: if the word “feared” is selected, then “they” refers to the city council. If “advocated” is selected, then “they” presumably refers to the demonstrators.
As the direct result Microsoft has significantly improved the MT-DNN approach to NLU, and finally surpassed the estimate for human performance on the overall average score on GLUE (87.6 vs. 87.1) on June 6, 2019. That happened a few days after I introduced you all to the indefatigable Alice and Bob.
I came from Philosophy of Language and develop Internal Relations theory of Analytic Philosophy. AI-parsing came straight from there and SQL n-gram from External theory.
I feel myself quite ready to discuss Moore, Russell and Wittgenstein, as well as Poincare, Bradley, Hegel, Spinoza, Nichola of Cusa and Maimonides, up to St.Paul, John and Ecclesiastes. They are whom I studied, this is my field.
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