Learn how to analyse TeraBytes of data in Real-Time with our "Principles of Real-Time Analytics" course

Build real-time analytics APIs in minutes, with no-backend involved.

Tinybird helps data teams deliver real-time answers at scale through SQL-based API endpoints.

  • ` $ curl \ -H "Authorization: Bearer $TOKEN" \ -X POST "https://api.tinybird.co/v0/datasources" \ -d "name=tripdata" \ --data-urlencode "url=https://s3.amazonaws.com/nyc-tlc/ trip+data/fhv_tripdata_2018-12.csv" > 24 million rows imported (33s) { "id": "da95d89a-3e00-4c8f-8324-590683472d08", "job_url": "https://api.tinybird.co/v0/jobs/da5-d9a", "status": "done" } $ curl \ -H "Authorization: Bearer $TOKEN" \ -X GET "https://api.tinybird.co/v0/sql" \ -d "q=SELECT pickup_datetime, dropoff_datetime FROM tripdata LIMIT 3 FORMAT PrettyCompact" > 24M rows proccesed, 2.03ms ┌─────pickup_datetime─┬────dropoff_datetime─┐ │ 2018-12-01 00:00:00 │ 2018-12-01 00:11:44 │ │ 2018-12-01 00:00:00 │ 2018-12-01 00:24:37 │ │ 2018-12-01 00:00:00 │ 2018-12-01 00:08:43 │ └─────────────────────┴─────────────────────┘ $`

  • `$ curl \ -H "Authorization: Bearer $TOKEN" \ -X POST "https://api.tinybird.co/v0/pipes" \ -d "name=avg_triptime_perday" \ -d "sql=SELECT toDayOfMonth(pickup_datetime) as day, avg(dateDiff('minute', pickup_datetime, dropoff_datetime)) as avg_trip_time_minutes FROM tripdata GROUP BY day" > Pipe created { "id": "t_8ab647ea74404e2f96173af3da01c6e0", "name": "avg_triptime_perday", "nodes": [ { "id": "t_3a11bf1e1f214ff99fc6ad2a6a4e98ff", "name": "avg_triptime_perday_0", "sql": "SELECT toDayOfMonth(pickup_datetime) as day, avg(dateDiff('minute', pickup_datetime, dropoff_datetime)) as avg_trip_time_minutes FROM tripdata GROUP BY day", "created_at": "2020-06-19 08:38:13.752960", "updated_at": "2020-06-19 08:38:13.752960" } ] "endpoint": null, "created_at": "2020-06-19 08:38:13.752936", "updated_at": "2020-06-19 08:38:13.752965" } $ curl \ -H "Authorization: Bearer $TOKEN" \ -X PUT \ -d t_3a11bf1e1f214ff99fc6ad2a6a4e98ff \ "https://api.tinybird.co/v0/pipes/avg_triptime_perday/ endpoint" > Pipe published! { "id": "t_8ab647ea74404e2f96173af3da01c6e0", "name": "avg_triptime_perday", "nodes": [...], "endpoint": "t_3a11bf1e1f214ff99fc6ad2a6a4e98ff", "created_at": "2020-06-19 08:38:13.752936", "updated_at": "2020-06-19 08:49:59.864445" } $`

  • `$ curl \ -H "Authorization: Bearer $TOKEN" \ "https://api.tinybird.co/v0/pipes/avg_trip_time_per_day.json" { "meta": [ { "name": "day", "type": "UInt8" }, { "name": "avg_trip_time_minutes", "type": "Float64" } ], "data": [ { "day": 1, "avg_trip_time_minutes": 20.70098973096046 }, { "day": 2, "avg_trip_time_minutes": 19.08052292398168 }, { "day": 3, "avg_trip_time_minutes": 22.520162824092775 }, { "day": 4, "avg_trip_time_minutes": 22.3515466837443 }, { "day": 5, "avg_trip_time_minutes": 22.452213124764377 }, { "day": 6, "avg_trip_time_minutes": 23.4411159622949 }, { "day": 7, "avg_trip_time_minutes": 23.51839854664563 }, { "day": 8, "avg_trip_time_minutes": 20.64550650689344 }, { "day": 9, "avg_trip_time_minutes": 18.921292837180122 }, { "day": 10, "avg_trip_time_minutes": 21.324635637380986 }, { "day": 11, "avg_trip_time_minutes": 23.11629047819647 }, { "day": 12, "avg_trip_time_minutes": -10.086464643835527 }, { "day": 13, "avg_trip_time_minutes": 24.118453469787116 }, { "day": 14, "avg_trip_time_minutes": 23.010015679887204 }, { "day": 15, "avg_trip_time_minutes": 20.25676140729181 }, { "day": 16, "avg_trip_time_minutes": 18.852047763245494 }, { "day": 17, "avg_trip_time_minutes": 21.91052995777931 }, { "day": 18, "avg_trip_time_minutes": 21.994984457945893 }, { "day": 19, "avg_trip_time_minutes": 22.503382566640187 }, { "day": 20, "avg_trip_time_minutes": 25.025137722956025 }, { "day": 21, "avg_trip_time_minutes": 21.831802450267173 }, { "day": 22, "avg_trip_time_minutes": 20.44439009816367 }, { "day": 23, "avg_trip_time_minutes": 18.892126829369115 }, { "day": 24, "avg_trip_time_minutes": -22.205200237225707 }, { "day": 25, "avg_trip_time_minutes": 16.861834216025397 }, { "day": 26, "avg_trip_time_minutes": 18.540556327822305 }, { "day": 27, "avg_trip_time_minutes": 19.711626897390726 }, { "day": 28, "avg_trip_time_minutes": 19.2635961329637 }, { "day": 29, "avg_trip_time_minutes": 18.911108347921576 }, { "day": 30, "avg_trip_time_minutes": 18.50702949637551 }, { "day": 31, "avg_trip_time_minutes": 18.2426204521323 } ], "rows": 31, "statistics": { "elapsed": 0.037134251, "rows_read": 23854144, "bytes_read": 190833152 } } $`

Fast & Smart

Ingest millions of rows per second. Fix import errors on-the-fly.

SQL based

Run embedded fast transformations using our Data Pipes.

Secure

Implement Data Source or row-level permissions using our Auth tokens.

No setup

No need for a backend to start building. Get started with some csv files.

Build in minutes,
not weeks

Ingest, query and build APIs for your data at scale in a matter of minutes. Forget about ETLs, performance and complex security rules.

  1. 1

    Ingest your data with ease

    Connect your data with our integrations or through the REST API. Transform or augment while you ingest if needed.
  2. 2

    Create your Pipes

    Query your data using Pipes, a new way chaining SQL queries designed to reduce most of the hassle.
  3. 3

    Publish your API endpoints

    Share access securely to your data in a click and get full OpenAPI and Postman documentation for your APIs.

Real-time is addictive

Implementing real-time analytics at scale enables an unprecedent number of new use cases with the potential to change entire industries

Build ultra low
latency ETLs
Personalize user experience
Train machine
learning models
Monitor and analyze
IoT networks
Ingest and transform data in real-time
Detect patterns with
ad-hoc queries

We're resolving millions of real-time API requests per day for...

For developers by developers

Imagine if you could turn any CSV file or Data Stream into a fully secured real-time analytics API endpoint in a matter of minutes. Connect your current database, data lake or data stream via CSV or the built-in integrations.

Tinybird cliTinybird UI

Accelerate data from almost anywhere

Connect and ingest data from Relational Databases, Data Warehouses and Data Streams easy and fast.

Amazon Redshift
Google BigQuery
MySQL
Snowflake

On the docs

Getting started with Tinybird

Learn how to build a quick and easy API endpoint using open data. It will not take you more than 10 minutes!

Read the guide