elements of computing

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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.
and 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 tokens like Golem (GNT) running on top of the Ethereum mainnet.
Another example is IP licensing tokens, running on the
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 and routinely store hundreds of Terabytes
and even Petabytes of data, with throughput that can exceed 1 million writes per second, like
.
Query languages like
are profound because they separate implementation from specification,
and are therefore not bound to any particular application.
. 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.
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.
is a public net instance of BigchainDB, with governance.
Also in the blockchain space, we can think of
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.
and are decentralized file systems that wrap decentralized or centralized blob storage.
, ,
, and do decentralized blob storage.
So does good old , though it uses a tit-for-tat scheme rather than tokens.
,
, and 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.
is an example protocol & network, on which data marketplaces can be built.
There are also application-specific marketplaces: for crypto markets,
for personal data; and for IoT streams.
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