It’s an ideal solution for environments that
require scalability, from edge devices with limited resources
to clusters processing massive amounts of data."
The World-best Performance
Edge Computing
Solving Developer Pain Points
sh -c "$(curl -fsSL https://machbase.com/install.sh)"
unzip machbase-neo-*.zip
<Click on the link below to download>
machbase-neo-v8.0.3-windows-amd64.zip
<Download from releases>
https://machbase.com/neo/releases/
machbase-neo serve
machbase-neo shell sql \
'create tag table EXAMPLE (\
name varchar(40) primary key, \
time datetime basetime, \
value double \
)'
curl
http://127.0.0.1:5654/db/query
\
--data-urlencode
\
"q=create tag table EXAMPLE (name varchar(40) primary
key, time datetime basetime, value double)"
machbase-neo shell sql \
"insert into EXAMPLE values('temperature',
1670380342000000000, 12.3456)"
curl
http://127.0.0.1:5654/db/query
\
--data-urlencode
\
"q=insert into EXAMPLE values('temperature',
1670380342000000000, 12.3456)"
import
requests
csvdata
=
"temperature,1670380342000000000,12.3456"
response =
requests.post(
"http://127.0.0.1:5654/db/write/EXAMPLE?heading=false",
data=csvdata,
headers={'Content-Type': 'text/csv'})
q =
"select * from example"
fetch(`http://127.0.0.1:5654/db/query?q=${encodeURIComponent(q)}`)
.then(res
=> {
return
res.json();
})
.then(data
=> {
console.log(data)
});
package main
import (
"net/http"
"bytes"
"strings"
)
func
main() {
rows :=
[]string{
"temperature,1670380342000000000,12.3456"}
http.Post(
"http://127.0.0.1:5654/db/write/EXAMPLE?heading=false",
"text/csv",
bytes.NewBufferString(strings.Join(rows,
"\n"))) }
using
HttpClient client =
new();
var
payload =
new
System.Net.Http.StringContent(
@"temperature,1677033057000000000,21.1
humidity,1677033057000000000,0.53",
new
System.Net.Http.Headers.MediaTypeHeaderValue("text/csv"));
var
rsp =
await
client.PostAsync(
"http://127.0.0.1:5654/db/write/example?heading=false", payload
);
machbase-neo shell sql 'select * from EXAMPLE'
curl
http://127.0.0.1:5654/db/query
\
--data-urlencode "q=select * from EXAMPLE"
import
requests
params = {"q":"select * from example",
"format":"csv",
"heading":"false"}
response =
requests.get("http://127.0.0.1:5654/db/query", params)
print(response.text)
q =
"select * from example"
fetch(`http://127.0.0.1:5654/db/query?q=${encodeURIComponent(q)}`)
.then(res
=> {
return
res.json();
})
.then(data
=> {
console.log(data)
});
package main
import (
"net/http"
"io"
)
func
main() {
q :=
url.QueryEscape("select * from example")
rsp, _ := http.Get("http://127.0.0.1:5654/db/query?format=csv&q="+q)
data,
_ := io.ReadAll(rsp.Body)
fmt.Println(string(data))
}
using
HttpClient client =
new();
var q =
System.Net.WebUtility.UrlEncode("select * from example");
var data =
await
client.GetStringAsync(
"http://127.0.0.1:5654/db/query?format=csv&q="+q
);
Console.Write(data);
Machbase was able to provide a real-time monitoring service by collecting and storing CSV files containing data from sensors on ship engines through a schema structure that fits time series data.
Using Machbase Time Series DB, we shortened the timeframe of a project to build an energy big data platform that collects and stores real-time power data to develop deep learning algorithms.
Machbase's reliable cluster operation has enabled Carrot's mileage insurance, which uses IoT devices, to collect real-time information on subscribers' vehicle operations and charge premiums based on that information.