This page provides a guide to Establishing a Connection to Apache CouchDB in CData Cloud, as well as information on the available resources, and a reference to the available connection properties.

Connecting to Apache CouchDB

Establishing a Connection shows how to authenticate to Apache CouchDB and configure any necessary connection properties to create a database in CData Cloud

Accessing Data from CData Cloud Services

Accessing data from Apache CouchDB through the available standard services and CData Cloud administration is documented in further details in the CData Cloud Documentation.

Connect to Apache CouchDB by selecting the corresponding icon in the Database tab. Required properties are listed under Settings. The Advanced tab lists connection properties that are not typically required.

Connecting to Apache CouchDB

Set the URL connection property to the URL of your Apache CouchDB instance. For example: http://localhost:5984

If you want your users (or JWTs) to have access only to specific databases, configure the admin_only_all_dbs option in your Apache CouchDB instance to grant all users access to the "/_all_dbs" endpoint, which is required by the Cloud for listing tables.

Authenticating to Apache CouchDB

• Basic: Basic username/password authentication.
• JWT: Authentication with a JWT.
• None: Anonymous access for databases that are public.

Basic Authentication

Set the following to connect to data:

• AuthScheme: Basic.
• User The Apache CouchDB user account used to authenticate.
• Password The Apache CouchDB password associated with the authenticating user.

JWT Authentication

Set AuthScheme to JWT.

You can either automatically generate (and, if applicable, refresh) a JWT or manually generate one:

Automatic Token Generation

Required

• JWTSubject: The name of the user to assign to the JWT.
• JWTAlgorithm: The algorithm to use for the JWT signature.
• JWTKeyType: The encryption key's type.
• JWTKey: The encryption key used to sign the JWT generated by the Cloud.

Optional

• JWTIssuer: The issuer of the JWT.
• JWTExpiration: The duration for which the JWT remains valid, in seconds.
• JWTHeaders: A collection of extra headers to include in the JWT header.
• JWTClaims: A collection of extra claims to include in the JWT payload.
• CredentialsLocation: The filepath of the settings file containing the JWT. If a settings file does not exist in this location, the Cloud creates a new settings file when it retrieves a JWT.

Manual Token Generation

You can generate the tokens yourself manually and pass them to the Cloud by using the JWTToken connection property.

Generating the Key Pair

When using asymmetric algorithms to sign the tokens, you must generate a private/public key pair. For that, a cryptographic library like OpenSSL can be used. For example:

# generate private key
openssl genrsa --out private_rsa256.pem 2048

# extract public key
openssl rsa -in private_rsa256.pem -pubout > public_rsa256.pem

JWT Configurations

Refer to CouchDB JWT Authentication Documentation for the following.

The alg and sub are required claims and will always be validated by the Apache CouchDB instance. Other required claims can be configured in the server (see required_claims). In that case, you must use JWTHeaders and JWTClaims so that the Cloud can include those additional claims when generating the JWT.

You can use roles_claim_name or the roles_claim_path options to assign roles to the JWTs.

An example configuration of the server and corresponding sample connection string are shown below:

Example Server Configuration

[chttpd]
...
authentication_handlers = {chttpd_auth, jwt_authentication_handler}, {chttpd_auth, cookie_authentication_handler}, {chttpd_auth, default_authentication_handler}
admin_only_all_dbs = false
...

[jwt_auth]
...
required_claims = exp
roles_claim_path = my.nested._couchdb\.roles
rsa:rsa_256 = -----BEGIN PUBLIC KEY-----\nYOUR_PUBLIC_KEY\n-----END PUBLIC KEY-----\n
...

Example Connection String

Url=http://localhost:5984;
JWTSubject=JWT User 1;
JWTAlgorithm=RS256;
JWTKeyType=PEMKEY_FILE;
JWTKey=PATH_TO_FOLDER\private_rsa256.pem;
JWTHeaders=kid : rsa_256 | Custom Header 1 : Test 1;
JWTClaims= my : eyJuZXN0ZWQiOnsiX2NvdWNoZGIucm9sZXMiOlsidXNlcjIiXX19 | Custom Claim 1 : Test 1;

Anonymous Authentication

Set the following to connect to data:

• AuthScheme: None.
• PublicDatabases: A comma-separated list of public databases to list as tables.

Inferring the Data Type

You can use the following properties to configure automatic data type detection, which is enabled by default.

• TypeDetectionScheme: You can use this property to enable or disable automatic type detection based on the value specified in RowScanDepth.
• RowScanDepth: This property determines the number of rows that will be scanned to determine column data types.

Apache CouchDB is a schema-less document database that provides high performance, availability, and scalability. These features are not necessarily incompatible with a standards-compliant query language like SQL-92. The following sections show various schemes that the Cloud offers to bridge the gap with relational SQL and a document database.

Automatic Schema Discovery

Parsing Nested Data

The Cloud models the schemaless Apache CouchDB objects into relational tables and translates SQL queries into Apache CouchDB queries to get the requested data.

Free-Form Queries

The schema of the table is necessary to report metadata, but you can write Free-Form Queries not tied to the schema to select, insert, update, or delete data from columns that do not exist in the schema (without flattening).

Vertical Flattening

See Vertical Flattening to process JSON arrays as separate tables.

JSON Functions

Query Mapping

See Query Mapping for more details on how various Apache CouchDB operations are represented as SQL.

Dynamic Views

The Cloud automatically infers a relational schema by inspecting a series of Apache CouchDB documents in a collection. You can use the RowScanDepth property to define the number of documents the Cloud will scan to do so. The columns identified during the discovery process depend on the FlattenArrays and FlattenObjects properties.

Flattening Objects

If FlattenObjects is set, all nested objects will be flattened into a series of columns. For example, consider the following document:

{
  id: 12,
  name: "Lohia Manufacturers Inc.",
  address: {street: "Main Street", city: "Chapel Hill", state: "NC"},
  offices: ["Chapel Hill", "London", "New York"],
  annual_revenue: 35,600,000
}

If FlattenObjects is not set, then the address.street, address.city, and address.state columns will not be broken apart. The address column of type string will instead represent the entire object. Its value would be {street: "Main Street", city: "Chapel Hill", state: "NC"}. See JSON Functions for more details on working with JSON aggregates.

You can change the separator character in the column name from a dot by setting SeparatorCharacter.

Flattening Arrays

The FlattenArrays property can be used to flatten array values into columns of their own. This is only recommended for arrays that are expected to be short, for example the coordinates below:

"coord": [ -73.856077, 40.848447 ]

It is best to leave other unbounded arrays as they are and piece out the data for them as needed using JSON Functions.

As discussed in Automatic Schema Discovery, intuited table schemas enable SQL access to unstructured Apache CouchDB data. JSON Functions enable you to use standard JSON functions to summarize Apache CouchDB data and extract values from any nested structures. However, you are not limited to these schemes.

After connecting you can query any nested structure without flattening the data. Any relations that you can access with FlattenArrays and FlattenObjects can also be accessed with an ad hoc SQL query.

Let's consider an example document from the following Restaurant data set:

 
{
  "address": {
    "building": "1007",
    "coord": [
      -73.856077,
      40.848447
    ],
    "street": "Morris Park Ave",
    "zipcode": "10462"
  },
  "borough": "Bronx",
  "cuisine": "Bakery",
  "grades": [
    {
      "grade": "A",
      "score": 2,
      "date": {
        "$date": "1393804800000"
      }
    },
    {
      "date": {
        "$date": "1378857600000"
      },
      "grade": "B",
      "score": 6
    },
    {
      "score": 10,
      "date": {
        "$date": "1358985600000"
      },
      "grade": "C"
    }
  ],
  "name": "Morris Park Bake Shop",
  "restaurant_id": "30075445"
} 

SELECT [address.building], [grades.1.grade] FROM restaurants WHERE restaurant_id = '30075445'

It is possible to retrieve an array of documents as if it were a separate table. Take the following JSON structure from the restaurants collection for example:

{
  "_id" : ObjectId("568c37b748ddf53c5ed98932"),
  "address" : {
    "building" : "1007",
    "coord" : [-73.856077, 40.848447],
    "street" : "Morris Park Ave",
    "zipcode" : "10462"
  },
  "borough" : "Bronx",
  "cuisine" : "Bakery",
  "grades" : [{
      "date" : ISODate("2014-03-03T00:00:00Z"),
      "grade" : "A",
      "score" : 2
    }, {
      "date" : ISODate("2013-09-11T00:00:00Z"),
      "grade" : "A",
      "score" : 6
    }, {
      "date" : ISODate("2013-01-24T00:00:00Z"),
      "grade" : "A",
      "score" : 10
    }, {
      "date" : ISODate("2011-11-23T00:00:00Z"),
      "grade" : "A",
      "score" : 9
    }, {
      "date" : ISODate("2011-03-10T00:00:00Z"),
      "grade" : "B",
      "score" : 14
    }],
  "name" : "Morris Park Bake Shop",
  "restaurant_id" : "30075445"
}

SELECT * FROM [restaurants.grades]

You may also want to include information from the base restaurants table. You can do this with a join. Flattened arrays can only be joined with the root document. The Cloud expects the left part of the join is the array document you want to flatten vertically. Set SupportEnhancedSQL to false to join nested Apache CouchDB documents -- this type of query is supported through the Apache CouchDB API.

SELECT [restaurants].[restaurant_id], [restaurants.grades].* FROM [restaurants.grades] JOIN [restaurants] WHERE [restaurants].name = 'Morris Park Bake Shop'

The Cloud can return JSON structures as column values. The Cloud enables you to use standard SQL functions to work with these JSON structures. The examples in this section use the following array:

[
     { "grade": "A", "score": 2 },
     { "grade": "A", "score": 6 },
     { "grade": "A", "score": 10 },
     { "grade": "A", "score": 9 },
     { "grade": "B", "score": 14 }
]

JSON_EXTRACT

SELECT Name, JSON_EXTRACT(grades,'[0].grade') AS Grade, JSON_EXTRACT(grades,'[0].score') AS Score FROM Students;

JSON_COUNT

SELECT Name, JSON_COUNT(grades,'[x]') AS NumberOfGrades FROM Students;

JSON_SUM

SELECT Name, JSON_SUM(score,'[x].score') AS TotalScore FROM Students;

JSON_MIN

SELECT Name, JSON_MIN(score,'[x].score') AS LowestScore FROM Students;

JSON_MAX

SELECT Name, JSON_MAX(score,'[x].score') AS HighestScore FROM Students;

DOCUMENT

The DOCUMENT function can be used to retrieve the entire document as a JSON string. See the following query and its result as an example:

SELECT DOCUMENT(*) FROM Customers;

{ "id": 12, "name": "Lohia Manufacturers Inc.", "address": { "street": "Main Street", "city": "Chapel Hill", "state": "NC"}, "offices": [ "Chapel Hill", "London", "New York" ], "annual_revenue": 35,600,000 }

The Cloud maps SQL queries into the corresponding Apache CouchDB queries. The Cloud uses the Selector syntax to compute the desired results.

A detailed description of all the transformations is out of scope, but we will describe some of the common elements that are used.

SELECT Queries

The SELECT statement is mapped to the GET and POST methods. Below are example queries and the corresponding request payloads.

SELECT *
FROM sales

SELECT _id, value
FROM sales

{
  "fields": [
    "_id",
    "value"
  ],
  "skip": 0,
  "selector": {
    "_id": {
      "$exists": true
    }
  }
}

SELECT * 
FROM sales 
WHERE value=175033291697

{
  "selector": {
    "value": {
      "$eq": 175033291697
    }
  },
  "skip": 0
}

SELECT * 
FROM sales 
WHERE value = 175033291697 OR month='June'

{
  "selector": {
    "$or": [
      {
        "value": {
          "$eq": 175033291697
        }
      },
      {
        "month": {
          "$eq": "June"
        }
      }
    ]
  },
  "skip": 0
}

SELECT * 
FROM sales
WHERE name LIKE 'A%'

{
  "selector": {
    "name": {
      "$regex": "A%"
    }
  },
  "skip": 0
}

SELECT * FROM sales
WHERE month='June'
ORDER BY _id ASC

{
  "skip": 0,
  "sort": [
    {
      "_id": "asc"
    }
  ],
  "selector": {
    "month": {
      "$eq": "June"
    }
  }
}

SELECT *
FROM sales
WHERE month='June'
ORDER BY _id DESC

{
  "skip": 0,
  "sort": [
    {
      "_id": "desc"
    }
  ],
  "selector": {
    "month": {
      "$eq": "June"
    }
  }
}

INSERT Statements

The INSERT statement is mapped to the HTTP POST request, as shown in the following query and request payload.

SQL Query

INSERT INTO users (_id, age, status, [address.city], [address.postalcode]) 
VALUES ('bcd001', 45, 'A', 'Chapel Hill', 27517)

Apache CouchDB Query

{
  "address": {
    "city": "Chapel Hill",
    "postalcode": 27517
  },
  "_id": "bcd001",
  "age": 45,
  "status": "A"
}

UPDATE Statements

The UPDATE statement is mapped to the HTTP PUT method, as shown in the following query and request payload.

SQL Query

UPDATE users 
SET status = 'C', [address.postalcode] = 90210
WHERE _id = 'bcd001'

Apache CouchDB Query

{
  "_id": "bcd001",
  "_rev": "1-446f6c67e3a483feae8eaf112f18892c",
  "status": "C",
  "age": 45,
  "address": {
    "city": "Chapel Hill",
    "postalcode": 90210
  }
}

DELETE Statements

The DELETE statement is mapped to the DELETE method as shown below.

SQL Query

DELETE FROM users WHERE _id = 'bcd001'

Apache CouchDB Query

For this query, a DELETE request is sent to the users/{_id}?rev={_rev} endpoint.

The Cloud maps types from Apache CouchDB to the Cloud's own data types. The table below documents these mappings.

The data type that some columns are regarded as by the Cloud is dynamically assessed based on the values in the column. Possible type determinations are shown as comma-separated values below.

The number of rows checked when determining the data type of a column is controlled by the RowScanDepth connection property.

You can query the system tables described in this section to access schema information, information on data source functionality, and batch operation statistics.

Schema Tables

The following tables return database metadata for Apache CouchDB:

• sys_catalogs: Lists the available databases.
• sys_schemas: Lists the available schemas.
• sys_tables: Lists the available tables and views.
• sys_tablecolumns: Describes the columns of the available tables and views.
• sys_procedures: Describes the available stored procedures.
• sys_procedureparameters: Describes stored procedure parameters.
• sys_keycolumns: Describes the primary and foreign keys.
• sys_indexes: Describes the available indexes.

Data Source Tables

The following tables return information about how to connect to and query the data source:

• sys_connection_props: Returns information on the available connection properties.
• sys_sqlinfo: Describes the SELECT queries that the Cloud can offload to the data source.

Query Information Tables

The following table returns query statistics for data modification queries:

• sys_identity: Returns information about batch operations or single updates.

Lists the available databases.

The following query retrieves all databases determined by the connection string:

SELECT * FROM sys_catalogs

Columns

Lists the available schemas.

The following query retrieves all available schemas:

          SELECT * FROM sys_schemas
          

Columns

Lists the available tables.

The following query retrieves the available tables and views:

          SELECT * FROM sys_tables
          

Columns

Describes the columns of the available tables and views.

The following query returns the columns and data types for the Movies table:

SELECT ColumnName, DataTypeName FROM sys_tablecolumns WHERE TableName='Movies' 

Columns

Lists the available stored procedures.

The following query retrieves the available stored procedures:

          SELECT * FROM sys_procedures
          

Columns

Describes stored procedure parameters.

The following query returns information about all of the input parameters for the SelectEntries stored procedure:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'SelectEntries' AND Direction = 1 OR Direction = 2

To include result set columns in addition to the parameters, set the IncludeResultColumns pseudo column to True:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'SelectEntries' AND IncludeResultColumns='True'

Columns

Pseudo-Columns

Describes the primary and foreign keys.

The following query retrieves the primary key for the Movies table:

         SELECT * FROM sys_keycolumns WHERE IsKey='True' AND TableName='Movies' 
          

Columns

Describes the foreign keys.

The following query retrieves all foreign keys which refer to other tables:

         SELECT * FROM sys_foreignkeys WHERE ForeignKeyType = 'FOREIGNKEY_TYPE_IMPORT'
          

Columns

Describes the primary keys.

The following query retrieves the primary keys from all tables and views:

         SELECT * FROM sys_primarykeys
          

Columns

Describes the available indexes. By filtering on indexes, you can write more selective queries with faster query response times.

The following query retrieves all indexes that are not primary keys:

          SELECT * FROM sys_indexes WHERE IsPrimary='false'
          

Columns

Returns information on the available connection properties and those set in the connection string.

The following query retrieves all connection properties that have been set in the connection string or set through a default value:

SELECT * FROM sys_connection_props WHERE Value <> ''

Columns

Describes the SELECT query processing that the Cloud can offload to the data source.

See SQL Compliance for SQL syntax details.

Discovering the Data Source's SELECT Capabilities

Below is an example data set of SQL capabilities. Some aspects of SELECT functionality are returned in a comma-separated list if supported; otherwise, the column contains NO.

The following query retrieves the operators that can be used in the WHERE clause:

SELECT * FROM sys_sqlinfo WHERE Name = 'SUPPORTED_OPERATORS'

Columns

Returns information about attempted modifications.

The following query retrieves the Ids of the modified rows in a batch operation:

         SELECT * FROM sys_identity
          

Columns

Describes the available system information.

The following query retrieves all columns:

SELECT * FROM sys_information

Columns

Views are similar to tables in the way that data is represented; however, views are read-only.

Queries can be executed against a view as if it were a normal table.

CData Cloud - Apache CouchDB Views

Retrieves detailed metadata about document revisions in CouchDB, including information on revision identifiers, history, and conflicts. This allows you to track document changes over time and manage version control effectively.

View-Specific Information

SELECT TableName FROM sys_tables;
-- MyDatabase1
-- MyDatabase1_DocumentRevisions
-- MyDatabase2
-- MyDatabase2_DocumentRevisions
-- ...

SELECT

SELECT * FROM MyDatabase1_DocumentRevisions;
-- The query executed internally: SELECT * FROM MyDatabase1_DocumentRevisions WHERE DocumentId IN (SELECT DocumentId FROM MyDatabase1);

, the Cloud will try to automatically retrieve the ids from the corresponding table (database). Note that this may quickly become costly in terms of performance when there are many DocumentId values (records) to fetch from that corresponding table.

In those cases, specifying only the DocumentId values that are of interest yourself should result in better performance. For example:

SELECT * FROM MyDatabase1_DocumentRevisions WHERE DocumentId = 'c1117cda61795fa7f11bd5f722151137';
SELECT * FROM MyDatabase1_DocumentRevisions WHERE DocumentId IN ('c1117cda61795fa7f11bd5f722151137', '7637ec6f1fe4e4e4d2cb080002002c6c');
SELECT * FROM MyDatabase1_DocumentRevisions WHERE DocumentId = 'c1117cda61795fa7f11bd5f722151137' AND RevisionId = '1-a6bbcd9244c7adc9e83c95887433048f';

Columns

Stored procedures are function-like interfaces that extend the functionality of the Cloud beyond simple SELECT/INSERT/UPDATE/DELETE operations with Apache CouchDB.

Stored procedures accept a list of parameters, perform their intended function, and then return any relevant response data from Apache CouchDB, along with an indication of whether the procedure succeeded or failed.

CData Cloud - Apache CouchDB Stored Procedures

Retrieves the full content of a CouchDB document as it existed in a specific revision. This enables you to view or work with the document’s state at a particular point in its revision history.

Input

Result Set Columns

Customizing the SSL Configuration

To enable TLS, set the following:

• URL: Prefix the connection string with https://

With this configuration, the Cloud attempts to negotiate TLS with the server. The server certificate is validated against the default system trusted certificate store. You can override how the certificate gets validated using the SSLServerCert connection property.

To specify another certificate, see the SSLServerCert connection property.

Connecting Through a Firewall or Proxy

HTTP Proxies

To authenticate to an HTTP proxy, set the following:

• ProxyServer: the hostname or IP address of the proxy server that you want to route HTTP traffic through.
• ProxyPort: the TCP port that the proxy server is running on.
• ProxyAuthScheme: the authentication method the Cloud uses when authenticating to the proxy server.
• ProxyUser: the username of a user account registered with the proxy server.
• ProxyPassword: the password associated with the ProxyUser.

Other Proxies

Set the following properties:

• To use a proxy-based firewall, set FirewallType, FirewallServer, and FirewallPort.
• To tunnel the connection, set FirewallType to TUNNEL.
• To authenticate, specify FirewallUser and FirewallPassword.
• To authenticate to a SOCKS proxy, additionally set FirewallType to SOCKS5.

The connection string properties are the various options that can be used to establish a connection. This section provides a complete list of the options you can configure in the connection string for this provider. Click the links for further details.

Authentication

JWT Authentication

SSL

Logging

Schema

Miscellaneous

This section provides a complete list of the Authentication properties you can configure in the connection string for this provider.

The type of authentication to use when connecting to Apache CouchDB.

Possible Values

Data Type

string

Default Value

"Basic"

Remarks

• Basic: Set this to use basic User/Password authentication.
• JWT: JWT authentication.
• None: No authentication is used.

The URL used to connect to the Apache CouchDB.

Data Type

string

Default Value

""

Remarks

The URL used to connect to the Apache CouchDB in the format http://{server}:{port}.

Specifies the authenticating user's user ID.

Data Type

string

Default Value

""

Remarks

The authenticating server requires both User and Password to validate the user's identity.

Specifies the authenticating user's password.

Data Type

string

Default Value

""

Remarks

The authenticating server requires both User and Password to validate the user's identity.

Specify a comma-separated list of public databases to list as tables.

Data Type

string

Default Value

""

Remarks

This is needed for anonymous access (AuthScheme=None) because the database listing call requires user authentication.

This section provides a complete list of the JWT Authentication properties you can configure in the connection string for this provider.

The JWT to use for authentication.

Data Type

string

Default Value

""

Remarks

If you have manually generated a JWT, you can provide it in this connection property. If a value is not supplied in this connection property, the Cloud generates the token itself.

The user subject for which the application is requesting delegated access.

Data Type

string

Default Value

""

Remarks

This is used as the sub claim in the JWT.

Apache CouchDB uses this as the user’s name when validating the JWT.

The issuer of the JWT.

Data Type

string

Default Value

""

Remarks

If not specified, this connection property defaults to the name of the Cloud, including version information.

The encryption algorithm used for signing the JWT.

Possible Values

Data Type

string

Default Value

"RS256"

Remarks

This is used as the alg claim in the JWT. This property can take one of the following values:

The amount of time until the JWT expires, in seconds.

Data Type

int

Default Value

-1

Remarks

This is used to calculate the exp claim in the JWT.

When set to -1, the Cloud generates the first token, but never refreshes it. This is the default value.

The type of the encryption key used for signing the JWT.

Possible Values

Data Type

string

Default Value

"PEMKEY_BLOB"

Remarks

This property can take one of the following values:

The encryption key for signing the JWT.

Data Type

string

Default Value

""

Remarks

The encryption key used for signing the JWT generated by the Cloud. The JWTKeyType field specifies the type of the key being used.

A collection of extra HTTP headers to include in the JWT header.

Data Type

string

Default Value

""

Remarks

The string should not contain any single quotes or double quotes.

The : character is a delimiter separating headers and their values, and the | character is a delimiter separating the header name-value pairs. End the list of headers with a semicolon. For example:

JWTHeaders = kid : key_1 | Custom Header 1 : value;

If you need to use more complex values such as JSON objects or arrays, they must be base64 encoded. For example:

JWTHeaders = kid : key_1 | my : eyJjdXN0b20iOlsianNvbiIsIm9iamVjdCJdfQ==;

By default, not all headers in the JWT are validated by Apache CouchDB (only alg). See the documentation of required_claims for information about enforcing the validation of additional headers.

A collection of extra claims to include in the JWT payload.

Data Type

string

Default Value

""

Remarks

The string should not contain any single quotes or double quotes.

The : character is a delimiter separating claims and their values, and the | character is a delimiter separating the name-value pairs of each claim. End the list of claims with a semicolon. For example:

JWTClaims = aud : https://my.couchdb.server | nbf : 1720444762;

If you need to use more complex values such as JSON objects or arrays, they have to be base64 encoded. For example:

JWTClaims = my : eyJuZXN0ZWQiOnsiX2NvdWNoZGIucm9sZXMiOlsidXNlcjIiXX19 | nbf : 1720444762;

By default, not all claims in the JWT are validated by Apache CouchDB (only alg). See the documentation of required_claims for information about enforcing the validation of additional claims.

The filepath of the settings file containing the JWT. If a settings file does not exist in this location, the provider creates a new settings file when it retrieves a JWT.

Data Type

string

Default Value

"%APPDATA%\\CData\\ApacheCouchDB Data Provider\\CredentialsFile.txt"

Remarks

If left unspecified, the default location is "<OS-dependent path prefix>\\CData\\ApacheCouchDB Data Provider\\CredentialsFile.txt", where <OS-dependent path prefix> is a different value depending on the operating system from which you are running the Cloud:

This section provides a complete list of the SSL properties you can configure in the connection string for this provider.

Specifies the certificate to be accepted from the server when connecting using TLS/SSL.

Data Type

string

Default Value

""

Remarks

If you are using a TLS/SSL connection, use this property to specify the TLS/SSL certificate to be accepted from the server. If you specify a value for this property, all other certificates that are not trusted by the machine are rejected.

This property can take the following forms:

Note: It is possible to use '*' to signify that all certificates should be accepted, but due to security concerns this is not recommended.

This section provides a complete list of the Logging properties you can configure in the connection string for this provider.

Specifies the verbosity level of the log file, which controls the amount of detail logged. Supported values range from 1 to 5.

Data Type

string

Default Value

"1"

Remarks

This property defines the level of detail the Cloud includes in the log file. Higher verbosity levels increase the detail of the logged information, but may also result in larger log files and slower performance due to the additional data being captured.

The default verbosity level is 1, which is recommended for regular operation. Higher verbosity levels are primarily intended for debugging purposes. For more information on each level, refer to Logging.

When combined with the LogModules property, Verbosity can refine logging to specific categories of information.

This section provides a complete list of the Schema properties you can configure in the connection string for this provider.

Optional setting that restricts the schemas reported to a subset of all available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC .

Data Type

string

Default Value

""

Remarks

Listing all available database schemas can take extra time, thus degrading performance. Providing a list of schemas in the connection string saves time and improves performance.

Whether to list views from Apache CouchDB or not.

Data Type

bool

Default Value

false

Remarks

Set this property to true for Apache CouchDB views to show up when listing tables.

This section provides a complete list of the Miscellaneous properties you can configure in the connection string for this provider.

Set FlattenArrays to the number of array elements to flatten into columns. Otherwise, arrays are returned as JSON strings.

Data Type

string

Default Value

""

Remarks

By default, nested arrays are returned as strings of JSON. The FlattenArrays property can be used to flatten the elements of nested arrays into columns of their own: Set FlattenArrays to the number of elements you want to return from nested arrays. The zero-based index is concatenated to the column name with a dot or the character specified by SeparatorCharacter. Other elements are ignored.

For example, you can return an arbitrary number of elements from an array of strings:

["FLOW-MATIC","LISP","COBOL"]

Setting FlattenArrays to -1 will flatten all the elements of nested arrays.

Using FlattenArrays is only recommended for arrays that are expected to be short. See NoSQL Database for other ways to access nested arrays.

Set FlattenObjects to true to flatten object properties into columns of their own. Otherwise, embedded objects as raw JSON strings.

Data Type

bool

Default Value

true

Remarks

The property name is concatenated onto the object name with a dot or the character specified by SeparatorCharacter.

For example, you can flatten the nested objects below at connection time:

[
  { "grade": "A", "score": 2 },
  { "grade": "A", "score": 6 },
  { "grade": "A", "score": 10 },
  { "grade": "A", "score": 9 },
  { "grade": "B", "score": 14 }
]

Set FlexibleSchema to true to scan for additional metadata on the query result set. Otherwise, the metadata will remain the same.

Data Type

bool

Default Value

true

Remarks

If false, the metadata will remain the same.

Specifies the maximum number of rows returned for queries that do not include either aggregation or GROUP BY.

Data Type

int

Default Value

-1

Remarks

The default value for this property, -1, means that no row limit is enforced unless the query explicitly includes a LIMIT clause. (When a query includes a LIMIT clause, the value specified in the query takes precedence over the MaxRows setting.)

Setting MaxRows to a whole number greater than 0 ensures that queries do not return excessively large result sets by default.

This property is useful for optimizing performance and preventing excessive resource consumption when executing queries that could otherwise return very large datasets.

Specifies the maximum number of records per page the provider returns when requesting data from Apache CouchDB.

Data Type

int

Default Value

1000

Remarks

When processing a query, instead of requesting all of the queried data at once from Apache CouchDB, the Cloud can request the queried data in pieces called pages.

This connection property determines the maximum number of results that the Cloud requests per page.

Note: Setting large page sizes may improve overall query execution time, but doing so causes the Cloud to use more memory when executing queries and risks triggering a timeout.

Specifies the pseudocolumns to expose as table columns, expressed as a string in the format 'TableName=ColumnName;TableName=ColumnName'.

Data Type

string

Default Value

""

Remarks

This property allows you to define which pseudocolumns the Cloud exposes as table columns.

To specify individual pseudocolumns, use the following format:

Table1=Column1;Table1=Column2;Table2=Column3

To include all pseudocolumns for all tables use:

*=*

The maximum number of rows to scan to look for the columns available in a table.

Data Type

int

Default Value

50

Remarks

The columns in a table must be determined by scanning table rows. This value determines the maximum number of rows that will be scanned.

Setting a high value may decrease performance. Setting a low value may prevent the data type from being determined properly, especially when there is null data.

The character or characters used to denote hierarchy.

Data Type

string

Default Value

"."

Remarks

In order to flatten out hierarchical structures, the Cloud needs some specifier that states the path to a column through the hierarchy. If this value is "." and a column comes back with the name address.city, this indicates that there is a mapped attribute with a child called city. If your data has columns that already use a single period within the attribute name, set the SeparatorCharacter to a different character or characters.

Specifies whether or not throws an exception if there is no rows updated.

Data Type

bool

Default Value

false

Remarks

Specifies whether or not throws an exception if there is no rows updated.

Specifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error.

Data Type

int

Default Value

60

Remarks

The timeout applies to each individual communication with the server rather than the entire query or operation. For example, a query could continue running beyond 60 seconds if each paging call completes within the timeout limit.

Timeout is set to 60 seconds by default. To disable timeouts, set this property to 0.

Disabling the timeout allows operations to run indefinitely until they succeed or fail due to other conditions such as server-side timeouts, network interruptions, or resource limits on the server.

Note: Use this property cautiously to avoid long-running operations that could degrade performance or result in unresponsive behavior.

Determines how the provider will scan the data to determine the fields and data types in each document collection.

Data Type

string

Default Value

"RowScan"

Remarks

Since Apache CouchDB is schema-less, the columns in a table must be determined by scanning table rows. Set TypeDetectionScheme to toggle the automatic discovery of data types. Set RowScanDepth to configure type detection.

See Also

Type detection is part of Automatic Schema Discovery. Set FlattenArrays and FlattenObjects to configure how the Cloud projects columns over the hierarchical data.

You can fine-tune the discovered columns and data types by calling CreateSchema to generate a schema file. Schema files have a simple format that makes it easy to change column behavior.

LZMA from 7Zip LZMA SDK

LZMA SDK is placed in the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or distribute the original LZMA SDK code, either in source code form or as a compiled binary, for any purpose, commercial or non-commercial, and by any means.

LZMA2 from XZ SDK

Version 1.9 and older are in the public domain.

Xamarin.Forms

Xamarin SDK

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