Querying with Orbital

Orbital focuses on querying for data based on it’s meaning, rather than which system provides it. This allows services to change, and data to move, without requiring consumers to update their queries.

Writing queries

Queries are written in TaxiQL, an open source query language for data.

TaxiQL is a great query language.

The taxi documentation has details on the syntax, which we haven’t duplicated here. Go check it out, then come back.

We’ll wait.

TaxiQL is agnostic of where data comes from - it’s left to Orbital to discover data from the various sources that have been connected.

Here’s some sample queries:

// Find all the movies
find { Movie[] }

// Find all the movies, enriching and projecting them to a different structure
find { Movie[] } as {
   title : MovieTitle
   director : DirectorName
   rating : RottenTomatoesScore


Projections are a way of taking data from one place, then transforming & combining it with other data sources.

Orbital uses the information present on the object being projected in order to call services and find other information.


model Purchase {
   transactionId : TransactionId
   customerId : CustomerId

find { Purchases[] }
as {
  // Projections let you change field names, and reshape objects as required
  txn: TransactionId
  // Not present on the original Purchase object, so try to
  // find it using something we already know (in this case, the CustomerId)
  customerName: CustomerName

Data discovery rules

When projecting, Orbital will use information present on the source object to discover data on the target object.

Data can be fetched from a single operation that returns the value, or by invoking a chain of operations to return the value.

Operations with @Id fields on return types

If the result of an operation is an object that exposes an @Id field, then only operations which accept that @Id field as an input will be called.


model Customer {
  @Id customerId : CustomerId
  name : CustomerName

service CustomerService {
   // Can be called when projecting, because
   // Person has an @Id of type PersonId

   // Cannot be called when projecting, because
   // Person has an @Id, and it isn't PersonName

Operations without @Id fields on return types

If the result of an operation is an object that does not expose an @Id field, then it can be called with any information available.

Filling in nulls

By default, if a service returns a null value, Orbital will accept it as-is.

However, if query annotates a field on a projection type with @FirstNotEmpty, Orbital will attempt to populate values by invoking operations to populate the missing values.

Orbital will execute a search using the other values present on the entity being projected as potential inputs to operations, and build a path to populate the missing values.

Operations are invoked following the standard Data Discovery Rules

Understanding caching in Orbital

By default, Orbital does not maintain a long-lived cache between operations, but you can add one by configuring an external cache - such as Redis or Hazelcast.

Without an external cache, Orbital caches operation calls for the lifetime of a query. This prevents the same operation being invoked repeatedly while projecting multiple rows in a result.

When caching, Responses are cached for a given operation + set of inputs. If an operation is invoked with different parameters, the cache is not used.

Operations that return an array of results, which return more than 10 values, will not have their responses cached. (This is not currently configurable, but reach out on slack if you need to configure this).

Recovering from failure

If an operation returns an error while Orbital is attempting to execute a query, then it is excluded from being invoked with the same parameters again. This exclusion is scoped to the query only, and expires at the end of the query.

After excluding the operation, Orbital will attempt to find another path to return the value being discovered.

Expressions in queries

Taxi allows the definition of expressions on both types and fields, but doesn’t provide an evaluation engine - that’s where Orbital comes in.

Typically, expressions are used in a projection within a query.

You can also use them on a model to expose derived information when a model is parsed by Orbital (eg., when return from a service) - but that’s less common. So, while documentation here focuses on query projections, you can do everything here on a model too.

Writing an expression in a projection

Expressions can be defined in the fields of a projected result from a query:

find { Flights[] }
as {
  flightNumber : FlightNumber
  totalSeatsAvailable : TotalSeats
  soldSeats : SoldSeats
  remainingSeats : Int = (this.totalSeatsAvailable - this.soldSeats)

Expressions can be defined in two ways - on a field, or on a type.

Expressions on a field

// Expression types on a field:
find { Flights[] }
as {
  flightNumber : FlightNumber
  totalSeatsAvailable : TotalSeats
  soldSeats : SoldSeats
  // field expressions can be defined EITHER using field references...
  remainingSeats : Int = (this.totalSeatsAvailable - this.soldSeats)
  // ...or type references...
  remainingSeats : Int = (TotalSeats - SoldSeats)

Expressions on a type

To encapsulate common expressions, you can define a type with the expression:

// Expression type:
type RemainingSeats = TotalSeats - SoldSeats

// Which is then used on a projection:
find { Flights[] }
as {
  flightNumber : FlightNumber
  totalSeatsAvailable : TotalSeats
  soldSeats : SoldSeats
  remainingSeats : RemainingSeats

Unlike field expressions, type expression cannot use field names, and can only reference other types.

How Orbital discovers values to evaluate expressions

When Orbital is evaluating an expression, it first looks on the source object being projected for the input values into the expression.

If any inputs are not available, then Orbital will perform a search using the current data available on the source object in an attempt to look up the value.

Submitting queries

Generally, developers will use the UI to write and test their queries, then integrate using Orbital’s rest API.

Rest API

Queries to Orbital are submitted to the /api/taxiql endpoint:

curl 'http://localhost:9022/api/taxiql' \
  -H 'Content-Type: application/taxiql' \
  --data-raw 'find { Movie[] }'

A word about content type

Strictly speaking, the content type for taxiql queries is application/taxiql. However, the Orbital server will accept taxiql queries with any of the following content types headers:

  • Content-Type: application/json
  • Content-Type: application/taxiql
  • Content-Type: text/plain

This is to allow broad compatability with clients.

Large queries with Server Sent Events

Running large queries can result in out-of-memory errors if Orbital is holding the result set in memory.

To address this, Orbital supports pushing results over server-sent-events. To consume a query as a server-sent-event, set the Accept header to text/event-stream:

curl 'http://localhost:9022/api/taxiql' \
  -H 'Accept: text/event-stream' \
  -H 'Content-Type: application/taxiql' \
  --data-raw 'find { Movie[] }'

Results are pushed out from Orbital as they are available.

Including type metadata in responses

Orbital can include type metadata in the responses being sent back.

To enable this, append ?resultMode=TYPED to the API call:

curl 'http://localhost:9022/api/taxiql?resultMode=TYPED' \
  -H 'Accept: text/event-stream' \
  -H 'Content-Type: application/taxiql' \
  --data-raw 'find { Movie[] }'

Defining output formats

By default, Orbital serves results to queries as JSON.

This can be configured to customize the result format.

With Accept headers

The following accept headers are supported:

HeaderResult type
`text/event-streamJSON with server-sent-events

Defining output formats with model formats

Fine-grained control is supported with custom model specs defined on model types. At present, only limited support is provided, but we plan to provide additional formats in a future release, along with the ability to register bespoke formats.

Formats are defined by adding an annotation to the model defined as the output type.

For example:

import io.vyne.formats.Csv

   delimiter = "|",
   nullValue = "NULL"
model Person {
   firstName : String by column("firstName")
   lastName : String by column("lastName")
   age : Int by column("age")

// Query:
// Response type (Person) contains a Csv format defined,
// which will be considered when writing responses.
find { Customer[] }
as { Person[] }


The full definition of the Csv model format is as follows:

ParameterDescriptionRequiredDefault Value
delimiterDefines the delimiter to use between columnsfalse,
firstRecordAsHeaderIndicates if the first line should be treated as a headerfalsetrue
nullValueDefines a custom token to use in place of nullfalsenull
containsTrailingDelimitersIndicates if the last delimiter is an empty column which should be ignoredfalsefalse
withQuoteDefines a quote character used if content needs to be escapedfalse