Sonnerie is a time-series database. Map a timestamp to a floating-point value. Store multiple of these series in a single database. Insert tens of millions of samples in minutes, on rotational media.
Sonnerie includes a Client API, which has its own API docs.
Sonnerie runs on Unix-like systems and is developed on Linux.
Sonnerie is designed to accept millions of samples across disparate series quickly, and then later fetch ranges from individual series. Memory is used for write-combining, write-ahead-logs are used to keep commits fast while still durable.
Fundamentally, the database is append-only. Edits and insertions are costly (and not yet implemented!).
You intake a lot of samples related to different entities all at once, and then want to read a lot of data for a entity, the disk usage patterns become very different
Timestamp | Entity 1 | Entity 2 | Entity 3 ------------------- | -------- | -------- | -------- 2000-01-01 00:00:00 | 50.0 | 23.0 | 95.3 2000-01-02 00:00:00 | | 24.0 | 2000-01-03 00:00:00 | 51.5 | 25.0 | 2000-01-04 00:00:00 | 53.0 | 26.0 | 94.8
At each timestamp (row), you insert some samples (it can be millions).
Some time later on, you want to run an analysis on a single Entity, Sonnerie allows one to quickly access all its values (an entire column).
Sonnerie is implemented in Rust, a systems programming language that runs
blazingly fast. Installation from source therefor requires you to
install the rust compiler,
which is as simple as: curl https://sh.rustup.rs -sSf | sh.
Sonnerie can then be installed from Cargo: cargo install sonnerie.
Sonnerie consists of one executable, sonnerie (~/.cargo/bin/sonnerie)
Just run Sonnerie, sonnerie start -d <database directory to use>.
Sonnerie is running in the background, listening on [::1]:5599 for connections.
Start the Sonnerie client:
sonnerie client
Start a transaction:
begin --write
Create a series:
create fibonacci
Add a few values to the series
add fibonacci 2018-01-01T00:00:00 1
add fibonacci 2018-01-02T00:00:00 1
add fibonacci 2018-01-03T00:00:00 2
add fibonacci 2018-01-04T00:00:00 3
add fibonacci 2018-01-05T00:00:00 5
add fibonacci 2018-01-06T00:00:00 8
Read some of those values back:
read fibonacci -f 2018-01-03 -t 2018-01-06
Sonnerie replies with:
2018-01-03 00:00:00 2
2018-01-04 00:00:00 3
2018-01-05 00:00:00 5
2018-01-06 00:00:00 8
Commit the transaction:
commit
After commit completes, the data is definitely on disk.
Try help and read --help (or --help with any command)
for more information.
Telnet into Sonnerie (telnet ::1 5599) and type "help" to see what you can
do. The protocol is text-based and very similar to the client frontend.
Commands use shell-like escaping, so spaces can be escaped with a backslash. Timestamps are milliseconds since the Unix Epoch.
The protocol formats floats with enough precision such that they can represent themselves exactly.
In order to ensure durability, many fsyncs need to be called (a few per
transaction). This can slow down imports. You should consider running sonnerie
prefixed with eatmydata,
which is a Debian package. It will temporarily suppress fsync. After
your import is done, start Sonnerie again normally.
When doing your inputs, tweak the size of the transaction until you find the optimal size. This might be a megabyte or so of data.
Online incremental backups are possible (the file format is designed accordingly) but not yet implemented.
You can do a full online backup as such, maintaining the following order:
mkdir dst
sqlite3 src/meta .dump | sqlite3 dst/meta
cp src/blocks dst/blocks
(This method will no longer apply once compacting is implemented).
Modifying existing data will be implemented shortly. It will result in wasted disk space and increased fragmentation.
Each sample requires 16 bytes on average plus small amounts of metadata.
Sonnerie was implemented by Charles Samuels at e.ventures Management LLC.