A time series database for big data
Try to use it with SDKs:
import time
import asyncio
from reduct import Client, Bucket
async def main():
client = Client('https://play.reduct-storage.dev')
bucket: Bucket = await client.create_bucket("my-bucket", exist_ok=True)
ts = time.time_ns() / 1000
await bucket.write("entry-1", b"Hey!!", ts)
data = await bucket.read("entry-1", ts)
print(data)
loop = asyncio.get_event_loop()
loop.run_until_complete(main())const {Client} = require("reduct-js")
const main = async () => {
const client = new Client("https://play.reduct-storage.dev");
const bucket = await client.getOrCreateBucket("bucket");
const ts = Date.now() * 1000;
await bucket.write("entry-1", "Hello, World!", ts);
data = await bucket.read("entry-1", ts);
console.log(data);
};
main()
.then(() => console.log("done"))
.catch((err) => console.error("oops: ", err));#include <reduct/client.h>
#include <iostream>
using reduct::IBucket;
using reduct::IClient;
int main() {
auto client = IClient::Build("https://play.reduct-storage.dev");
// Create a bucket
auto [bucket, create_err] = client->GetOrCreateBucket("bucket");
// Write some data
IBucket::Time ts = IBucket::Time::clock::now();
auto write_err = bucket->Write("entry-1", "some_data1", ts);
// Read data
auto [blob, read_err] = bucket->Read("entry-1", ts);
if (!read_err) {
std::cout << "Read blob: " << blob << std::endl;
}
}# Create a bucket
curl -d "{\"quota_type\":\"FIFO\", \"quota_size\":10000}" \
-X POST \
-a https://play.reduct-storage.dev/b/my_data
# Write some data
curl -d "some_data" \
-X POST \
-a https://play.reduct-storage.dev/b/my_data/entry_1?ts=10000
# Read the data by timestamp
curl https://play.reduct-storage.dev/b/my_data/entry_1?ts=10000
