REST API

The QuestDB REST API is based on standard HTTP features and is understood by off-the-shelf HTTP clients. It provides a simple way to interact with QuestDB and is compatible with most programming languages. API functions are fully keyed on the URL and they use query parameters as their arguments.

The Web Console is the official Web client relying on the REST API. Find out more in the section using the Web Console.

Available methods

/imp for importing data from .CSV files
/exec to execute a SQL statement
/exp to export data

Examples

QuestDB exposes a REST API for compatibility with a wide range of libraries and tools. The REST API is accessible on port 9000 and has the following insert-capable entrypoints:

Entrypoint	HTTP Method	Description	API Docs
`/imp`	POST	Import CSV data	Reference
`/exec?query=..`	GET	Run SQL Query returning JSON result set	Reference

For details such as content type, query parameters and more, refer to the REST API docs.

`/imp`: Uploading Tabular Data

Let's assume you want to upload the following data via the /imp entrypoint:

CSV
Table

col1,col2,col3
a,10.5,True
b,100,False
c,,True

col1	col2	col3
a	10.5	true
b	100	false
c	NULL	true

You can do so via the command line using cURL or programmatically via HTTP APIs in your scripts and applications.

By default, the response is designed to be human-readable. Use the fmt=json query argument to obtain a response in JSON. You can also specify the schema explicitly. See the second example in Python for these features.

cURL
Python
NodeJS
Go

This example imports a CSV file with automatic schema detection.

Basic import with table name

curl -F data=@data.csv http://localhost:9000/imp?name=table_name

This example overwrites an existing table and specifies a timestamp format and a designated timestamp column. For more information on the optional parameters to specify timestamp formats, partitioning and renaming tables, see the REST API documentation.

Providing a user-defined schema
curl \
-F schema='[{"name":"ts", "type": "TIMESTAMP", "pattern": "yyyy-MM-dd - HH:mm:ss"}]' \
-F data=@weather.csv 'http://localhost:9000/imp?overwrite=true&timestamp=ts'

This first example shows uploading the data.csv file with automatic schema detection.

import sys
import requests

csv = {'data': ('my_table', open('./data.csv', 'r'))}
host = 'http://localhost:9000'

try:
    response = requests.post(host + '/imp', files=csv)
    print(response.text)
except requests.exceptions.RequestException as e:
    print(f'Error: {e}', file=sys.stderr)

The second example creates a CSV buffer from Python objects and uploads them with a custom schema. Note UTF-8 encoding.

The fmt=json parameter allows us to obtain a parsable response, rather than a tabular response designed for human consumption.

import io
import csv
import requests
import pprint
import json


def to_csv_str(table):
    output = io.StringIO()
    csv.writer(output, dialect='excel').writerows(table)
    return output.getvalue().encode('utf-8')


def main():
    table_name = 'example_table2'
    table = [
        ['col1', 'col2', 'col3'],
        ['a',    10.5,   True],
        ['b',    100,    False],
        ['c',    None,   True]]

    table_csv = to_csv_str(table)
    print(table_csv)
    schema = json.dumps([
        {'name': 'col1', 'type': 'SYMBOL'},
        {'name': 'col2', 'type': 'DOUBLE'},
        {'name': 'col3', 'type': 'BOOLEAN'}])
    response = requests.post(
        'http://localhost:9000/imp',
        params={'fmt': 'json'},
        files={
            'schema': schema,
            'data': (table_name, table_csv)}).json()

    # You can parse the `status` field and `error` fields
    # of individual columns. See Reference/API/REST docs for details.
    pprint.pprint(response)


if __name__ == '__main__':
    main()

const fetch = require("node-fetch")
const FormData = require("form-data")
const fs = require("fs")

const HOST = "http://127.0.0.1:9000"

async function run() {
  const form = new FormData()

  form.append("data", fs.readFileSync(__dirname + "/data.csv"), {
    filename: "data.csv",
    contentType: "application/octet-stream",
  })

  try {
    const r = await fetch(`${HOST}/imp`, {
      method: "POST",
      body: form,
      headers: form.getHeaders(),
    })

    console.log(r)
  } catch (e) {
    console.error(e)
  }
}

run()

package main

import (
  "bytes"
  "fmt"
  "io"
  "io/ioutil"
  "log"
  "mime/multipart"
  "net/http"
  "net/url"
  "os"
)

func main() {
  u, err := url.Parse("http://localhost:9000")
  checkErr(err)
  u.Path += "imp"
  url := fmt.Sprintf("%v", u)
  fileName := "/path/to/data.csv"
  file, err := os.Open(fileName)
  checkErr(err)

  defer file.Close()

  buf := new(bytes.Buffer)
  writer := multipart.NewWriter(buf)
  uploadFile, _ := writer.CreateFormFile("data", "data.csv")
  _, err = io.Copy(uploadFile, file)
  checkErr(err)
  writer.Close()

  req, err := http.NewRequest(http.MethodPut, url, buf)
  checkErr(err)
  req.Header.Add("Content-Type", writer.FormDataContentType())

  client := &http.Client{}
  res, err := client.Do(req)
  checkErr(err)

  defer res.Body.Close()

  body, err := ioutil.ReadAll(res.Body)
  checkErr(err)

  log.Println(string(body))
}

func checkErr(err error) {
  if err != nil {
    panic(err)
  }
}

`/exec`: SQL `INSERT` Query

The /exec entrypoint takes a SQL query and returns results as JSON.

We can use this for quick SQL inserts too, but note that there's no support for parameterized queries that are necessary to avoid SQL injection issues. Prefer InfluxDB Line Protocol if you need high-performance inserts.

cURL
Python
NodeJS
Go

# Create Table
curl -G \
  --data-urlencode "query=CREATE TABLE IF NOT EXISTS trades(name STRING, value INT)" \
  http://localhost:9000/exec

# Insert a row
curl -G \
  --data-urlencode "query=INSERT INTO trades VALUES('abc', 123456)" \
  http://localhost:9000/exec

import sys
import requests
import json

host = 'http://localhost:9000'

def run_query(sql_query):
    query_params = {'query': sql_query, 'fmt' : 'json'}
    try:
        response = requests.get(host + '/exec', params=query_params)
        json_response = json.loads(response.text)
        print(json_response)
    except requests.exceptions.RequestException as e:
        print(f'Error: {e}', file=sys.stderr)

# create table
run_query("CREATE TABLE IF NOT EXISTS trades (name STRING, value INT)")
# insert row
run_query("INSERT INTO trades VALUES('abc', 123456)")

The node-fetch package can be installed using npm i node-fetch.

const fetch = require("node-fetch")

const HOST = "http://127.0.0.1:9000"

async function createTable() {
  try {
    const query = "CREATE TABLE IF NOT EXISTS trades (name STRING, value INT)"

    const response = await fetch(
      `${HOST}/exec?query=${encodeURIComponent(query)}`,
    )
    const json = await response.json()

    console.log(json)
  } catch (error) {
    console.log(error)
  }
}

async function insertData() {
  try {
    const query = "INSERT INTO trades VALUES('abc', 123456)"

    const response = await fetch(
      `${HOST}/exec?query=${encodeURIComponent(query)}`,
    )
    const json = await response.json()

    console.log(json)
  } catch (error) {
    console.log(error)
  }
}

createTable().then(insertData)

package main

import (
  "fmt"
  "io/ioutil"
  "log"
  "net/http"
  "net/url"
)

func main() {
  u, err := url.Parse("http://localhost:9000")
  checkErr(err)

  u.Path += "exec"
  params := url.Values{}
  params.Add("query", `
    CREATE TABLE IF NOT EXISTS
      trades (name STRING, value INT);
    INSERT INTO
      trades
    VALUES(
      "abc",
      123456
    );
  `)
  u.RawQuery = params.Encode()
  url := fmt.Sprintf("%v", u)

  res, err := http.Get(url)
  checkErr(err)

  defer res.Body.Close()

  body, err := ioutil.ReadAll(res.Body)
  checkErr(err)

  log.Println(string(body))
}

func checkErr(err error) {
  if err != nil {
    panic(err)
  }
}

/imp - Import data

/imp streams tabular text data directly into a table. It supports CSV, TAB and pipe (|) delimited inputs with optional headers. There are no restrictions on data size. Data types and structures are detected automatically, without additional configuration. In some cases, additional configuration can be provided to improve the automatic detection as described in user-defined schema.

note

The structure detection algorithm analyses the chunk in the beginning of the file and relies on relative uniformity of data. When the first chunk is non-representative of the rest of the data, automatic imports can yield errors.

If the data follows a uniform pattern, the number of lines which are analyzed for schema detection can be reduced to improve performance during uploads using the http.text.analysis.max.lines key. Usage of this setting is described in the HTTP server configuration documentation.

URL parameters

/imp is expecting an HTTP POST request using the multipart/form-data Content-Type with following optional URL parameters which must be URL encoded:

Parameter	Required	Default	Description
`atomicity`	No	`skipCol`	`abort`, `skipRow` or `skipCol`. Behaviour when an error is detected in the data. `abort`: the entire file will be skipped. `skipRow`: the row is skipped. `skipCol`: the column is skipped.
`delimiter`	No		URL encoded delimiter character. When set, import will try to detect the delimiter automatically. Since automatic delimiter detection requires at least two lines (rows) to be present in the file, this parameter may be used to allow single line file import.
`fmt`	No	`tabular`	Can be set to `json` to get the response formatted as such.
`forceHeader`	No	`false`	`true` or `false`. When `false`, QuestDB will try to infer if the first line of the file is the header line. When set to `true`, QuestDB will expect that line to be the header line.
`name`	No	Name of the file	Name of the table to create, see below.
`overwrite`	No	`false`	`true` or `false`. When set to true, any existing data or structure will be overwritten.
`partitionBy`	No	`NONE`	See partitions.
`o3MaxLag`	No		Sets upper limit on the created table to be used for the in-memory out-of-order buffer. Can be also set globally via the `cairo.o3.max.lag` configuration property.
`maxUncommittedRows`	No		Maximum number of uncommitted rows to be set for the created table. When the number of pending rows reaches this parameter on a table, a commit will be issued. Can be also set globally via the `cairo.max.uncommitted.rows` configuration property.
`skipLev`	No	`false`	`true` or `false`. Skip “Line Extra Values”, when set to true, the parser will ignore those extra values rather than ignoring entire line. An extra value is something in addition to what is defined by the header.
`timestamp`	No		Name of the column that will be used as a designated timestamp.
`create`	No	`true`	`true` or `false`. When set to `false`, QuestDB will not automatically create a table '`name`' if one does not exist, and will return an error instead.

Example usage

curl -F data=@weather.csv \
'http://localhost:9000/imp?overwrite=true&name=new_table&timestamp=ts&partitionBy=MONTH'

Further example queries with context on the source CSV file contents relative and the generated tables are provided in the examples section below.

Names

Table and column names are subject to restrictions, the following list of characters are automatically removed:

[whitespace]
.
?
,
:
\
/
\\
\0
)
(
_
+
-
*
~
%

When the header row is missing, column names are generated automatically.

Consistency guarantees

/imp benefits from the properties of the QuestDB storage model, although Atomicity and Durability can be relaxed to meet convenience and performance demands.

Atomicity

QuestDB is fully insured against any connection problems. If the server detects closed socket(s), the entire request is rolled back instantly and transparently for any existing readers. The only time data can be partially imported is when atomicity is in relaxed mode and data cannot be converted to column type. In this scenario, any "defective" row of data is discarded and /imp continues to stream request data into table.

Consistency

This property is guaranteed by consistency of append transactions against QuestDB storage engine.

Isolation

Data is committed to QuestDB storage engine at end of request. Uncommitted transactions are not visible to readers.

Durability

/imp streams data from network socket buffer directly into memory mapped files. At this point data is handed over to the OS and is resilient against QuestDB internal errors and unlikely but hypothetically possible crashes. This is default method of appending data and it is chosen for its performance characteristics.

Examples

Automatic schema detection

The following example uploads a file ratings.csv which has the following contents:

ts	visMiles	tempF	dewpF
2010-01-01T00:00:00.000000Z	8.8	34	30
2010-01-01T00:51:00.000000Z	9.100000000000	34	30
2010-01-01T01:36:00.000000Z	8.0	34	30
...	...	...	...

An import can be performed with automatic schema detection with the following request:

curl -F data=@weather.csv 'http://localhost:9000/imp'

A HTTP status code of 200 will be returned and the response will be:

+-------------------------------------------------------------------------------+
|      Location:  |     weather.csv  |        Pattern  | Locale  |      Errors  |
|   Partition by  |            NONE  |                 |         |              |
|      Timestamp  |            NONE  |                 |         |              |
+-------------------------------------------------------------------------------+
|   Rows handled  |           49976  |                 |         |              |
|  Rows imported  |           49976  |                 |         |              |
+-------------------------------------------------------------------------------+
|              0  |              ts  |                TIMESTAMP  |           0  |
|              1  |        visMiles  |                   DOUBLE  |           0  |
|              2  |           tempF  |                      INT  |           0  |
|              3  |           dewpF  |                      INT  |           0  |
+-------------------------------------------------------------------------------+

User-defined schema

To specify the schema of a table, a schema object can be provided:

curl \
-F schema='[{"name":"dewpF", "type": "STRING"}]' \
-F data=@weather.csv 'http://localhost:9000/imp'

Response
+------------------------------------------------------------------------------+
|      Location:  |    weather.csv  |        Pattern  | Locale  |      Errors  |
|   Partition by  |           NONE  |                 |         |              |
|      Timestamp  |           NONE  |                 |         |              |
+------------------------------------------------------------------------------+
|   Rows handled  |          49976  |                 |         |              |
|  Rows imported  |          49976  |                 |         |              |
+------------------------------------------------------------------------------+
|              0  |             ts  |                TIMESTAMP  |           0  |
|              1  |       visMiles  |                   DOUBLE  |           0  |
|              2  |          tempF  |                      INT  |           0  |
|              3  |          dewpF  |                   STRING  |           0  |
+------------------------------------------------------------------------------+

Non-standard timestamp formats

Given a file weather.csv with the following contents which contains a timestamp with a non-standard format:

ts	visMiles	tempF	dewpF
2010-01-01 - 00:00:00	8.8	34	30
2010-01-01 - 00:51:00	9.100000000000	34	30
2010-01-01 - 01:36:00	8.0	34	30
...	...	...	...

The file can be imported as usual with the following request:

Importing CSV with non-standard timestamp

curl -F data=@weather.csv 'http://localhost:9000/imp'

A HTTP status code of 200 will be returned and the import will be successful, but the timestamp column is detected as a VARCHAR type:

Response with timestamp as VARCHAR type
+-------------------------------------------------------------------------------+
|      Location:  |     weather.csv  |        Pattern  | Locale  |      Errors  |
|   Partition by  |            NONE  |                 |         |              |
|      Timestamp  |            NONE  |                 |         |              |
+-------------------------------------------------------------------------------+
|   Rows handled  |           49976  |                 |         |              |
|  Rows imported  |           49976  |                 |         |              |
+-------------------------------------------------------------------------------+
|              0  |              ts  |                  VARCHAR  |           0  |
|              1  |        visMiles  |                   DOUBLE  |           0  |
|              2  |           tempF  |                      INT  |           0  |
|              3  |           dewpF  |                      INT  |           0  |
+-------------------------------------------------------------------------------+

To amend the timestamp column type, this example curl can be used which has a schema JSON object to specify that the ts column is of TIMESTAMP type with the pattern yyyy-MM-dd - HH:mm:ss

Additionally, URL parameters are provided:

overwrite=true to overwrite the existing table
timestamp=ts to specify that the ts column is the designated timestamp column for this table
partitionBy=MONTH to set a partitioning strategy on the table by MONTH

Providing a user-defined schema
curl \
-F schema='[{"name":"ts", "type": "TIMESTAMP", "pattern": "yyyy-MM-dd - HH:mm:ss"}]' \
-F data=@weather.csv \
'http://localhost:9000/imp?overwrite=true&timestamp=ts&partitionBy=MONTH'

The HTTP status code will be set to 200 and the response will show 0 errors parsing the timestamp column:

+------------------------------------------------------------------------------+
|      Location:  |    weather.csv  |        Pattern  | Locale  |      Errors  |
|   Partition by  |          MONTH  |                 |         |              |
|      Timestamp  |             ts  |                 |         |              |
+------------------------------------------------------------------------------+
|   Rows handled  |          49976  |                 |         |              |
|  Rows imported  |          49976  |                 |         |              |
+------------------------------------------------------------------------------+
|              0  |             ts  |                TIMESTAMP  |           0  |
|              1  |       visMiles  |                   DOUBLE  |           0  |
|              2  |          tempF  |                      INT  |           0  |
|              3  |          dewpF  |                      INT  |           0  |
+------------------------------------------------------------------------------+

JSON response

If you intend to upload CSV programmatically, it's easier to parse the response as JSON. Set fmt=json query argument on the request.

Here's an example of a successful response:

{
  "status": "OK",
  "location": "example_table",
  "rowsRejected": 0,
  "rowsImported": 3,
  "header": false,
  "columns": [
    { "name": "col1", "type": "SYMBOL", "size": 4, "errors": 0 },
    { "name": "col2", "type": "DOUBLE", "size": 8, "errors": 0 },
    { "name": "col3", "type": "BOOLEAN", "size": 1, "errors": 0 }
  ]
}

Here is an example with request-level errors:

{
  "status": "not enough lines [table=example_table]"
}

Here is an example with column-level errors due to unsuccessful casts:

{
  "status": "OK",
  "location": "example_table2",
  "rowsRejected": 0,
  "rowsImported": 3,
  "header": false,
  "columns": [
    { "name": "col1", "type": "DOUBLE", "size": 8, "errors": 3 },
    { "name": "col2", "type": "SYMBOL", "size": 4, "errors": 0 },
    { "name": "col3", "type": "BOOLEAN", "size": 1, "errors": 0 }
  ]
}

/exec - Execute queries

/exec compiles and executes the SQL query supplied as a parameter and returns a JSON response.

note

The query execution terminates automatically when the socket connection is closed.

Overview

Parameters

/exec is expecting an HTTP GET request with following query parameters:

Parameter	Required	Default	Description
`count`	No	`false`	`true` or `false`. Counts the number of rows and returns this value.
`limit`	No		Allows limiting the number of rows to return. `limit=10` will return the first 10 rows (equivalent to `limit=1,10`), `limit=10,20` will return row numbers 10 through to 20 inclusive.
`nm`	No	`false`	`true` or `false`. Skips the metadata section of the response when set to `true`.
`query`	Yes		URL encoded query text. It can be multi-line.
`timings`	No	`false`	`true` or `false`. When set to `true`, QuestDB will also include a `timings` property in the response which gives details about the execution times.
`explain`	No	`false`	`true` or `false`. When set to `true`, QuestDB will also include an `explain` property in the response which gives details about the execution plan.
`quoteLargeNum`	No	`false`	`true` or `false`. When set to `true`, QuestDB will surround `LONG` type numbers with double quotation marks that will make them parsed as strings.

The parameters must be URL encoded.

Headers

Supported HTTP headers:

Header	Required	Description
`Statement-Timeout`	No	Query timeout in milliseconds, overrides default timeout from server.conf

Examples

SELECT query example:

curl -G \
  --data-urlencode "query=SELECT timestamp, tempF FROM weather LIMIT 2;" \
  --data-urlencode "count=true" \
  http://localhost:9000/exec

A HTTP status code of 200 is returned with the following response body:

{
  "query": "SELECT timestamp, tempF FROM weather LIMIT 2;",
  "columns": [
    {
      "name": "timestamp",
      "type": "TIMESTAMP"
    },
    {
      "name": "tempF",
      "type": "INT"
    }
  ],
  "timestamp": 0
  "dataset": [
    ["2010-01-01T00:00:00.000000Z", 34],
    ["2010-01-01T00:51:00.000000Z", 34]
  ],
  "count": 2
}

SELECT query returns response in the following format:

{
  "query": string,
  "columns": Array<{ "name": string, "type": string }>
  "dataset": Array<Array<Value for Column1, Value for Column2>>,
  "timestamp": number,
  "count": Optional<number>,
  "timings": Optional<{ compiler: number, count: number, execute: number }>,
  "explain": Optional<{ jitCompiled: boolean }>
}

You can find the exact list of column types in the dedicated page.

The timestamp field indicates which of the columns in the result set is the designated timestamp, or -1 if there isn't one.

UPDATE query example:

This request executes an update of table weather setting 2 minutes query timeout

curl -G \
  -H "Statement-Timeout: 120000" \
  --data-urlencode "query=UPDATE weather SET tempF = tempF + 0.12 WHERE tempF > 60" \
  http://localhost:9000/exec

A HTTP status code of 200 is returned with the following response body:

{
  "ddl": "OK",
  "updated": 34
}

CREATE TABLE query example:

This request creates a basic table, with a designated timestamp.

curl -G \
  -H "Statement-Timeout: 120000" \
  --data-urlencode "query=CREATE TABLE foo ( a INT, ts TIMESTAMP) timestamp(ts)" \
  http://localhost:9000/exec

A HTTP status code of 200 is returned with the following response body:

{
  "ddl": "OK"
}

/exp - Export data

This endpoint allows you to pass url-encoded queries but the request body is returned in a tabular form to be saved and reused as opposed to JSON.

Overview

/exp is expecting an HTTP GET request with following parameters:

Parameter	Required	Description
`query`	Yes	URL encoded query text. It can be multi-line.
`limit`	No	Paging opp parameter. For example, `limit=10,20` will return row numbers 10 through to 20 inclusive and `limit=20` will return first 20 rows, which is equivalent to `limit=0,20`. `limit=-20` will return the last 20 rows.
`nm`	No	`true` or `false`. Skips the metadata section of the response when set to `true`.

The parameters must be URL encoded.

Examples

Considering the query:

curl -G \
  --data-urlencode "query=SELECT AccidentIndex2, Date, Time FROM 'Accidents0514.csv'" \
  --data-urlencode "limit=5" \
  http://localhost:9000/exp

A HTTP status code of 200 is returned with the following response body:

"AccidentIndex","Date","Time"
200501BS00001,"2005-01-04T00:00:00.000Z",17:42
200501BS00002,"2005-01-05T00:00:00.000Z",17:36
200501BS00003,"2005-01-06T00:00:00.000Z",00:15
200501BS00004,"2005-01-07T00:00:00.000Z",10:35
200501BS00005,"2005-01-10T00:00:00.000Z",21:13

Error responses

Malformed queries

A successful call to /exec or /exp which also contains a malformed query will return response bodies with the following format:

{
  "query": string,
  "error": string,
  "position": number
}

The position field is the character number from the beginning of the string where the error was found.

Considering the query:

curl -G \
  --data-urlencode "query=SELECT * FROM table;" \
  http://localhost:9000/exp

A HTTP status code of 400 is returned with the following response body:

{
  "query": "SELECT * FROM table;",
  "error": "function, literal or constant is expected",
  "position": 8
}

Authentication (RBAC)

note

Role-based Access Control (RBAC) is available in QuestDB Enterprise. See the next paragraph for authentication in QuestDB Open Source.

REST API supports two authentication types:

HTTP basic authentication
Token-based authentication

The first authentication type is mainly supported by web browsers. But you can also apply user credentials programmatically in a Authorization: Basic header. This example curl command that executes a SELECT 1; query along with the Authorization: Basic header:

curl -G --data-urlencode "query=SELECT 1;" \
    -u "my_user:my_password" \
    http://localhost:9000/exec

The second authentication type requires a REST API token to be specified in a Authorization: Bearer header:

curl -G --data-urlencode "query=SELECT 1;" \
    -H "Authorization: Bearer qt1cNK6s2t79f76GmTBN9k7XTWm5wwOtF7C0UBxiHGPn44" \
    http://localhost:9000/exec

Refer to the user management page to learn more on how to generate a REST API token.

Authentication in QuestDB open source

QuestDB Open Source supports HTTP basic authentication. To enable it, set the configuration options http.user and http.password in server.conf.

The following example shows how to enable HTTP basic authentication in QuestDB open source:

http.user=my_user
http.password=my_password

Then this curl command executes a SELECT 1; query:

curl -G --data-urlencode "query=SELECT 1;" \
    -u "my_user:my_password" \
    http://localhost:9000/exec

Examples​

/imp: Uploading Tabular Data​

/exec: SQL INSERT Query​

/imp - Import data​

URL parameters​

Names​

Consistency guarantees​

Atomicity​

Consistency​

Isolation​

Durability​

Examples​

Automatic schema detection​

User-defined schema​

JSON response​

/exec - Execute queries​

Overview​

Parameters​

Headers​

Examples​

SELECT query example:​

UPDATE query example:​

CREATE TABLE query example:​

/exp - Export data​

Overview​

Examples​

Error responses​

Malformed queries​

Authentication (RBAC)​

Authentication in QuestDB open source​

Examples

`/imp`: Uploading Tabular Data

`/exec`: SQL `INSERT` Query

/imp - Import data

URL parameters

Names

Consistency guarantees

Atomicity

Consistency

Isolation

Durability

Examples

Automatic schema detection

User-defined schema

JSON response

/exec - Execute queries

Overview

Parameters

Headers

Examples

SELECT query example:

UPDATE query example:

CREATE TABLE query example:

/exp - Export data

Overview

Examples

Error responses

Malformed queries

Authentication (RBAC)

Authentication in QuestDB open source