a tool for compiling a SQL database based on confirmed transactions, from past IOTA DBs.
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parse_and_store.py initial commit Aug 28, 2017
readme.md update DB source URL Jul 2, 2018
setup.py initial commit Aug 28, 2017
transaction.py initial commit Aug 28, 2017
traverse.py Add X-IOTA-API-Version header Dec 2, 2017



iotaWayBack is a tool for compiling a SQL database based on confirmed transactions, from past IOTA DBs.

In addition, it's a tool to document the process I did, to create my copy of this SQL DB - a continuous database of confirmed transaction from Oct. 4 2016 - Oct. 20 2017.

if you only want to search my DB, without building your own - jump to 4.

from IRI to SQL:

1. obtaining past IOTA DBs:

All pre-snapshot dbs can be found here: https://dbfiles.iota.org/?prefix=mainnet/IOTA_DBs/.

More information on the DB collection process can be found here.
*credit to @lobeto, who reached out to veteran IOTA users to complete the missing DBs.

2. traversing confirmed transactions & dumping raw trytes:

in each IOTA DB you will find an iri.jar file, matching the version used back when the database was used.

and a start.bat file with an appropriate command to spin-up the node.

for each IOTA DB you want to dump:

  1. start IRI node.
  2. run python traverse.py.
  3. (stop IRI node)

this will create a .dmp file with <hash>,<raw_trytes> for each IRI version, which will be parsed by the next stage.

each IOTA_DB zip also contains the .dmp file computed on by me, if you want to skip this stage.

3. importing transaction into database:

after completing all IOTA DB dumps continue to importing

You have a choice of DBEngine between: sqlite & MySQL.

  • sqlite is a local DB, no setup required.
  • MySQL requires running a server, but is more performant.

given the size of the DB (~4M entries), I went with MySQL. as MySQL requires a server, I assume if you chose this option, you know how to setup a schema (iotaWayBack) & manage user privileges (user, password in parse_and_store.py).

  1. run pip install -e .
  2. set DBEngine in parse_and_store.py according to your DB Engine decision above.
  3. (if you have the .dmp files in a different folder, set folder in parse_and_store.py accordingly.)
  4. run python parse_and_store.py

this will create a table transactions that has each confirmed transaction with parsed fields.

4. using the SQL DB:

I have a version of this process running. contact me on iota's slack, if you want to skip all the above steps & just access the data.

now you can open the SQL DB with your favorite client. my GUI favorites:

or the packaged CLI tools: sqlite, mysql.

Example queries:

SELECT * FROM iotaWayBack.transactions WHERE address='YOURADDRESS'; // get all the transations associated with a given address.
SELECT count(*) FROM (SELECT DISTINCT address FROM iotaWayBack.transactions GROUP BY address) as A; // count all unique address in IOTA.
SELECT * FROM iotaWayBack.transactions WHERE timestampDate>'2017/08/05' AND timestampDate<'2017/08/06'; // get all transaction in a given time window.