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elements of computing

1. storage

token storage

Tokens are stores of value

(e.g. assets, securities) whether it’s Bitcoins, air miles, or digital art copyright.

The main actions on a token storage system are

to issue and transfer tokens (with many variants), while preventing double-spends and the like.

⁠

Bitcoin⁠

and

Zcash⁠

are two prominent “pure play” systems focusing solely on tokens.

Ethereum happens to use tokens in service towards its mission of being a world computer.

These are all examples of tokens given out as internal incentives to run the network infrastructure.

Other tokens aren’t internal to a network to power the network itself,

but are used for incentives in a higher-level network where the lower-level infrastructure actually stores the tokens.

One example is

ERC20⁠

tokens like Golem (GNT) running on top of the Ethereum mainnet.

Another example is

Envoke’s⁠

IP licensing tokens, running on the

IPDB⁠

network.

Finally, I have listed a “

.*⁠

” to illustrate that most blockchain systems have a mechanism for token storage.

database

Databases specialize in storing structured metadata,

for example as tables (relational DB),

document stores (e.g. JSON),

key-value stores,

time series,

or graphs;

and then rapidly retrieving that data via queries (e.g. SQL).

Traditional distributed (but centralized) databases like

MongoDB⁠

and

Cassandra⁠

routinely store hundreds of Terabytes

and even Petabytes of data, with throughput that can exceed 1 million writes per second, like

here⁠

Query languages like

SQL⁠

are profound because they separate implementation from specification,

and are therefore not bound to any particular application.

⁠

SQL has been a standard for decades⁠

. This is why the same database system can be used across many different industries.

Put another way: to generalize beyond Bitcoin to more applications without any application-specific code,

you don’t need to go all the way to Turing completeness. You just need a database.

This has corresponding benefits in simplicity and scale.

⁠

BigchainDB⁠

is decentralized database software; specifically a document store. Being built on MongoDB (or RethinkDB), it inherits the querying and scale of Mongo. But it also has blockchain-y characteristics like decentralized control, tamper-resistance, and token support.

IPDB⁠

is a public net instance of BigchainDB, with governance.

Also in the blockchain space, we can think of

IOTA⁠

as a time-series database, if we squint a bit.

file system / data blob storage

These are systems to store large files (movies, mp3s, large datasets), organized in a hierarchy of directories and files.

⁠

IPFS⁠

and

Tahoe-LAFS⁠

are decentralized file systems that wrap decentralized or centralized blob storage.

⁠

FileCoin⁠

Storj⁠

Sia⁠

, and

Tieron⁠

do decentralized blob storage.

So does good old

BitTorrent⁠

, though it uses a tit-for-tat scheme rather than tokens.

⁠

Ethereum Swarm⁠

Dat⁠

, and

Swarm-JS⁠

do basically both.

data marketplace

These systems connect the data owners (e.g. enterprises) with data consumers (e.g. AI startups).

While they’re higher-level than databases and file systems, they are nonetheless core infrastructure

because the countless applications that need data (e.g. anything AI) will depend on such services.

⁠

Ocean⁠

is an example protocol & network, on which data marketplaces can be built.

There are also application-specific marketplaces:

Enigma Catalyst⁠

for crypto markets,

⁠

Datum⁠

for personal data; and

DataBroker DAO⁠

for IoT streams.

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