Why blockchain detractors are missing the point
And so it goes on. From popular posts to contemptuous tweets to predictions about the future, the world and its mother are lining up to throw tomatoes at private blockchains, before even understanding what they are.
Saying that a private blockchain is just a shared database is like saying that HTML and HTTP are “just” distributed hypertext. It’s wrong in two ways. First, the semantic one: private blockchains are a technology that enables shared databases, like pens enable writing and HTML/HTTP enable distributed hypertext. The bitcoin blockchain and its primary application cannot be meaningfully separated, because one could not exist without the other. But this equivalence does not apply to private blockchains at all.
The second mistake is the use of the word “just”. Just? Were HTML and HTTP just a way to do distributed hypertext? Hypertext was invented decades earlier, so are these technologies a minor footnote in computer history? Oh but let me count the ways in which they earned their place: (a) a simple markup language that any layperson could learn, (b) a hierarchical addressing scheme that works both with TCP/IP and our conceptual model of place, (c) a simple protocol for the state-free retrieval of content, and (d) both client and server software that brought the whole thing to life. We might as well say that Newton was just a scientist and Dostoyevsky just a writer.
So let’s make this perfectly clear: Yes, private blockchains are just a way to share a database. But they enable a new type of shared database, with huge implications for the financial world and beyond. And if you’re willing to read on, I’m going to tell you exactly why.
What is a database?
A database is a repository of structured information, organized into tables. You can think of it as a collection of one or more Excel spreadsheets, which can optionally be linked together. Each table contains information about a set of entities of a particular type, with one entity per row. Each table also has one or more columns, which describe different aspects of those entities. For example, the table for WidgetCo’s internal staff directory might have columns for employee ID, first name, last name, department, internal phone number and room number.
One of the important ways in which databases go beyond spreadsheets is that they contain rules about the data stored within. These rules help ensure that the information remains sane and consistent for the benefit of the entire organization. In today’s most popular databases, the rules take a number of common forms:
- The database schema defines what kind of information is permitted in each column. For example, the phone number must contain 4 digits and cannot be left blank (“null”).
- Unique keys which state that a particular column (e.g. employee ID) must have a different value in every row.
- Check constraints which enforce relationships between the column values in each row. For example, if the department is “Procurement” then the room number must start with a 3 or 4.
- Foreign keys which enforce relationships between tables. For example, if the database contains another table used for payroll, there might be a rule that every employee ID in the payroll table must also exist in the staff directory.
A transaction is a collection of changes to a database that is accepted or rejected as a whole. Every time a transaction modifies the database, the software ensures that the database’s rules are followed. If any part of a transaction violates one of these rules, the entire transaction will be rejected with a corresponding error.
There are other more esoteric rule types I could list, but they all have one thing in common. They answer the question: Is the database in a valid state? In other words, they act as a constraint on the database’s contents when viewed at a single point in time. And this works just fine for a database which sits inside a single organization, because the main job of the constraints is to prevent programmer error. If one of WidgetCo’s internal applications tried to insert a 3-digit phone number into the directory, this wouldn’t be due to malice, but rather a bug in the developer’s thinking or code. The ability of a database to catch these mistakes is undoubtedly handy, and helps prevent bad information propagating within an organization, but it doesn’t fix problems of trust. (Constraints can also help simplify application logic, for example via foreign key cascading or on-duplicate clauses, but these are still just ways to help developers.)
Now let’s think about how WidgetCo’s internal staff directory might be shared with the outside world. In many cases, there is no problem providing shared read access. The directory can be exported to a text file and emailed to customers and suppliers. It can be posted on the Internet, just like this one. It can even be given an API to allow searching by external code. Shared read is a technical doddle, a question of deciding who can see what.
But things start getting stickier when we think about shared write. What if WidgetCo wants an external entity to modify its database? Perhaps the phones are being replaced by PhoneCo, who will then update the phone numbers in the staff directory. In this case, WidgetCo would create a new “account” for PhoneCo to use. Unlike accounts for WidgetCo’s internal use, PhoneCo’s account is only permitted to change the phone number column, and never add or delete rows. All of PhoneCo’s transactions are processed by WidgetCo’s database system, which now applies two types of restriction:
- Global rules which apply to all database users. For example, the phone company can’t change a number to contain only 3 digits, and neither can anybody else.
- Per-account rules restricting what PhoneCo is permitted to do, in this case only modifying the phone number column of existing rows.
So far, so good. We have a shared write database. It works because WidgetCo is in charge of the database and the phone company gains access by virtue of WidgetCo’s good grace. If PhoneCo started setting phone numbers randomly, WidgetCo can shut down their access, terminate their contract, and restore some old data from a backup. And if WidgetCo started misbehaving, say by reversing the new phone numbers entered by PhoneCo, well that would be entirely pointless, since it would only harm WidgetCo themselves. The phone company would consider WidgetCo to be a peculiar customer but not particularly care, so long as they paid their bill on time.
But now let’s see what happens if two or more parties want to share a database which (a) none of the parties controls, (b) can be written to by any party, and (c) can be relied upon by everyone. To make things worse, let’s say that these parties have different incentives, don’t trust each other and may even be fierce competitors. In this case, the solution has always been the same: introduce a trusted intermediary. This intermediary manages a database centrally, provides accounts to all of the parties, and ensures that all operations are permitted according to a known set of rules. In many cases, especially financial, every party still maintains its own copy of the data, so everyone spends a lot of time checking that their databases agree.
It all gets rather messy and cumbersome. But if we’re talking about a shared write database in an environment of limited trust, there is currently no alternative. That’s one of the main reasons why financial transactions go through central clearing houses, why you use Google Calendar even in a small workgroup, and why the crowd-sourced wonder that is Wikipedia spends millions of dollars on hosting. Even as the user interface of the web moves to the client side, centralized servers continue to store the data on which those interfaces rely.
Real shared write
So let’s say that we wanted to allow a database to be shared, in a write sense, without a central authority. For example, several competing companies want to maintain a joint staff directory for the benefit of their mutual customers. What might that actually look like? Well, it would need a number of things:
- A robust peer-to-peer network that allows transactions to be created by any party and propagated quickly to all connected nodes.
- A way to identify conflicts between transactions and resolve them automatically.
- A synchronization technology that ensures all peers converge on an identical copy of the database.
- A method for tagging different pieces of information as belonging to different participants, and enforcing this form of data ownership without a central authority.
- A paradigm for expressing restrictions on which operations are permitted, e.g. to prevent one company from inflating the directory with fictitious entries.
Whew. That’s a tough list right there, and it’s simply not supported by today’s off-the-shelf databases. Current peer-to-peer replication technology is clumsy and has a complex approach to conflict resolution. Those databases that do support row-based security still require a central authority to enforce it. And standard database-level restrictions like unique keys and check constraints cannot protect a database against malicious modifications. The bottom line is this:
We need a whole bunch of new stuff for shared write databases to work, and it just so happens that blockchains provide them.
I won’t go into too much detail about how blockchains do these things, because I’ve covered much of it before. Some key elements include regular peer-to-peer techniques, grouping transactions into blocks, one-way cryptographic hash functions, a multi-party consensus algorithm, distributed multiversion concurrency control and per-row permissions based on public key cryptography. A long list of old ideas combined in a new way. HTML/HTTP, if you like.
In addition to all of these, shared write databases require an entirely new type of rule, to restrict the transformations that a transaction can perform. This is an absolutely key innovation, and makes all the difference if we’re sharing a database between non-trusting entities. These types of rules can be expressed as bitcoin-style transaction constraints or Ethereum-style enforced stored procedures (“smart contracts”), each of which has advantages and disadvantages. Perhaps there are other better ways waiting to be discovered. But they all share the property of tying together the database’s state before and after a transaction takes place. In other words, they answer the question: Was that a valid transaction? This is fundamentally different from asking whether the database is valid at a single point in time.
If you’re wondering if this type of database has useful real-world applications, well that’s a fair question. But you might note the intense interest in private blockchains from one sector at least, because of their potential for simplifying processes and reducing costs and delays. Financial institutions are heavy users of today’s database platforms, and those platforms do not enable a shared write scenario. This is what banks are looking for.
This problem and its solution have absolutely nothing to do with bitcoin and the idea of censorship-free money. In fact, the only connection to bitcoin is the technical similarity between the bitcoin blockchain and how some of these private blockchains are implemented today. One key difference is that private blockchains don’t need proof of work mining, since blocks are created by a closed set of identified participants. Over time the two worlds may well diverge further, because their requirements are completely different. Whether you like financial regulation or not, the simple fact is that private blockchains are potentially useful in a regulated world, whereas for now at least, public blockchains are not.
If I may finish with an analogy, the UN Declaration on the Principles of International Law does not tell countries that they can hold any territory they want, so long as it’s surrounded by a clearly-marked fence. Rather, it states that “No territorial acquisition resulting from the threat or use of force shall be recognized as legal”. In other words, it’s a rule regarding the legitimacy of changes, not just of situations. And the UN declaration, which seems so obvious to us now, was a complete revolution in international law. It meant a world no longer based on unilateral power and authority, but one where differences can be resolved by mutual consensus.
When it comes to shared databases, private blockchains do exactly the same thing.
Binance to make changes as ‘trader’ scams liquidity on ETHUSD Futures
A tweet by the VP of Futures at Binance, Aaron Gong, addressed an apparent attack on the liquidity of USDETH Perpetual Futures.
As per the tweet by Gong, Binance believes this to be ‘intentional sabotage’ from a competitor and stated that,
“This happened on ETHUSD Perp futures. It was caused by one trader, both ways. We believe this may be intentional sabotage from a competitor. The trader lost lots of money himself. But also caused other stop orders to trigger. We will make a few changes to reduce in the future.”
Given the state of the order book, many believed it was incredulous to claim that one single trader could scam the entire liquidity.
a whale can manipulate a price on any exchange, what you can do is set your stop loss to mark price not (last price).
— cryptoSha (@Mewz_Ashea) October 29, 2020
Binance stated that they would make several changes to ensure this situation does not arise again in the future.
Binance will change the stop order to default to Mark (index) Price and not Last Price to avoid this problem. They will also turn on Price Protection for all stop orders so that if Last Price and Mark Price differs significantly, stop orders will trigger.
The exchange also stated that they would incentivize more market makers to provide liquidity and order book depth so that this situation will be unlikely to arise once again.
The chart above depicts Exchange 24-hour ETH Futures Volumes, indicating Binance is the exchange with the second-highest volume in this category. However, their claim that a lack of liquidity and order book depth was a potential cause of this issue, suggests otherwise.
CZ, CEO of Binance, also tweeted on the issue stating that the proposed changes in light of this issue would have “a material impact for Futures users”.
DFI.Money (YFII) Reaches Double-Bottom, Struggles to Hold Support
DFI.Money (YFII) has been, for the most part, decreasing since Sept 12. It appeared to have reversed its trend at the beginning of October but has since fallen back to its daily all-time low. Whether or not YFII bounces at the current support level will be a strong indication of new negative price discovery or […]
The post DFI.Money (YFII) Reaches Double-Bottom, Struggles to Hold Support appeared first on BeInCrypto.
DFI.Money (YFII) has been, for the most part, decreasing since Sept 12. It appeared to have reversed its trend at the beginning of October but has since fallen back to its daily all-time low.
Whether or not YFII bounces at the current support level will be a strong indication of new negative price discovery or reversal of the trend.
YFII Begins To Bounce
On Oct 7, YFII reached a low of $1,169. It began an upward move shortly afterward, reaching a high of $2,585 after only two days, measuring a total increase of 120% since the lows. However, YFII has been gradually falling back.
At the time of press, YFII was trading below the 0.786 Fib level of $1,470. This Fib level is also very near to the previous resistance area, creating a strong support level between $1,400-$1,470.
Short-term technical indicators are bullish. Both the RSI and MACD have generated considerable bullish divergence, the former being inside its oversold region, a sign that a reversal is likely near.
Therefore, YFII is expected to bounce upwards from the current support level.
In addition, it seems that YFII is trading inside a descending wedge and has been doing so since Oct 10. Since the wedge is considered a bullish reversal pattern, a breakout is expected.
If YFII begins moving upwards and breaks out from the wedge, the closest resistance levels would be found at $2,500 and $3,050.
Cryptocurrency trader @CryptoTony_ outlined a YFII chart, stating that the price will likely decrease once more towards $1,400 before initiating a rapid upward movement towards $3,600.
With the aforementioned Oct 7 low, it seems that YFII successfully completed an A-B-C corrective formation (shown in black below).
The movement afterward (highlighted) looks impulsive, so it is possible that YFII began an upward trend that will take the price to the resistance levels at $2,500 and $3,050.
A closer look reveals a completed five-wave formation and an ensuing A-B-C corrective structure (both shown in red).
Furthermore, waves A:C have a 1:1.61 ratio, which is very common in such corrections. This supports the possibility that YFII has reached a bottom and will now begin to increase.
A decrease below the wave 1 low of $1,169 would invalidate this particular wave count.
To conclude, it is possible that YFII has begun a new upward movement and will increase towards the resistance levels outlined above.
Disclaimer: Cryptocurrency trading carries a high level of risk and may not be suitable for all investors. The views expressed in this article do not reflect those of BeInCrypto.
Bitcoin to Surpass $20,000 ATH By Early 2021 According to Raul Pal
Former hedge fund manager and CEO of Real Vision, Raoul Pal, believes that the real impact of the COVID-19 pandemic is about to reach the financial markets. By outlining several upcoming cornerstones among traditional financial assets, he highlighted Bitcoin as the “life raft” in this situation.
Raoul Pal: Everything Has Changed
In a recent Twitter thread, the Wall Street veteran outlined the rapidly growing COVID-19 cases worldwide. The total number of infected has neared 45 million, while the death toll is almost 1,2 million.
Pal predicted that these rising numbers in Europe, the US, and Canada are about to “exert economic pressures and extinguish the Hope phase of reflation dreams.” He believes that the upcoming consequences will harm the economy even more than the early 2020 developments. A real economic recovery “will take more than a post-election stimulus in January.”
He continued by looking at several markets that have started to feel the adverse consequences and have fallen to long-term support levels. Those included the oil price, Spain’s benchmark stock market index – the IBEX 35, the EU Banks Index, the euro, the British pound, the US dollar, and more.
As such, he broached a few possible solutions – “you can buy bonds and dollars, or you can take the life raft – Bitcoin.”
“Or, to dampen the volatility of a risk-off event (we can and will see sharp BTC corrections), you can have all three for a near-perfect portfolio for this phase.” – Pal concluded.
Bitcoin Will Eat The World And Price Predictions From Pal
Pal further highlighted his positive views on Bitcoin by saying the cryptocurrency “will eat the world.” He attributed it to its performance, which is so dominant and so “all-encompassing” that it will “suck in every single asset narrative dry and spit it out.”
“Never before in my career have I seen a trade so dominant that holding any other assets makes almost no sense.”
As far as price predictions go, Pal said that $14,000 is the only resistance left in Bitcoin’s way to the all-time high at $20,000. He expects that BTC should overcome the December 2017 high by “early next year at the latest.”
Additionally, CryptoPotato recently reported an even more optimistic and long-term forecast. By using a regression on the logarithmic chart since inception, Pal brought up a model that sees Bitcoin reaching $1 million by 2025.
Featured Image Courtesy of BusinessInsider
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