docs/website/versioned_docs/version-1.11.x/components/data-connectors/dynamodb.md at fb7b1cb5614e5f05a1506b0acea35a42bb303834 · spiceai/docs

title

DynamoDB Data Connector

sidebar_label

DynamoDB Data Connector

description

DynamoDB Data Connector Documentation

Configuration

`from`

The from field should specify the DynamoDB table name:

`from`	Description
`dynamodb:table`	Read data from a DynamoDB table named `table`

:::note If an expected table is not found, verify the dynamodb_aws_region parameter. DynamoDB tables are region-specific. :::

`name`

The dataset name. This will be used as the table name within Spice.

Example:

datasets:
  - from: dynamodb:users
    name: my_users
    params: ...

SELECT COUNT(*) FROM my_users;

The dataset name cannot be a reserved keyword.

`params`

The DynamoDB data connector supports the following configuration parameters:

Parameter Name	Description
`dynamodb_aws_region`	Required. The AWS region containing the DynamoDB table
`dynamodb_aws_access_key_id`	Optional. AWS access key ID for authentication. If not provided, credentials will be loaded from environment variables or IAM roles
`dynamodb_aws_secret_access_key`	Optional. AWS secret access key for authentication. If not provided, credentials will be loaded from environment variables or IAM roles
`dynamodb_aws_session_token`	Optional. AWS session token for authentication
`dynamodb_aws_auth`	Optional. Authentication method. Use `iam_role` (default) for IAM role-based authentication or `key` for explicit access key credentials.
`dynamodb_aws_iam_role_source`	Optional. IAM role credential source (only used when `dynamodb_aws_auth: iam_role`). `auto` (default) uses the default AWS credential chain, `metadata` uses only instance/container metadata (IMDS, ECS, EKS/IRSA), `env` uses only environment variables
`unnest_depth`	Optional. Maximum nesting depth for unnesting embedded documents into a flattened structure. Higher values expand deeper nested fields.
`schema_infer_max_records`	Optional. The number of documents to use to infer the schema. Defaults to 10
`scan_segments`	Optional. Number of segments for `Scan` request. 'auto' by default, which will calculate number of segments based on number of the records in a table
`time_format`	Optional. Go-style time format used for parsing/formatting timestamps. See Time Format

Authentication

The DynamoDB connector supports two authentication methods controlled by the dynamodb_aws_auth parameter:

datasets:
  - from: dynamodb:my_table
    params:
      dynamodb_aws_auth: iam_role | key                   # iam_role is default
      dynamodb_aws_iam_role_source: auto | metadata | env # auto is default (only used with iam_role)

IAM Role Authentication (`dynamodb_aws_auth: iam_role`)

This is the default authentication method. When using IAM role authentication, the dynamodb_aws_iam_role_source parameter controls which credential sources are used:

Source Value	Description	Credential Sources
`auto` (default)	Uses the default AWS credential chain	All sources listed below, in order
`metadata`	Uses only instance/container metadata	Web Identity Token, ECS Container Credentials, EC2 Instance Metadata (IMDSv2)
`env`	Uses only environment variables	`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_SESSION_TOKEN`

:::note When using iam_role authentication, any explicitly provided access keys (dynamodb_aws_access_key_id, dynamodb_aws_secret_access_key) are ignored. :::

Key-Based Authentication (`dynamodb_aws_auth: key`)

When dynamodb_aws_auth is set to key, credentials must be provided explicitly:

datasets:
  - from: dynamodb:my_table
    params:
      dynamodb_aws_auth: key
      dynamodb_aws_access_key_id: ${secrets:aws_access_key_id}
      dynamodb_aws_secret_access_key: ${secrets:aws_secret_access_key}
      dynamodb_aws_session_token: ${secrets:aws_session_token}  # Optional, for temporary credentials

Default Credential Chain (`auto`)

When using dynamodb_aws_auth: iam_role with dynamodb_aws_iam_role_source: auto (or when both parameters are omitted), credentials are loaded from the following sources in order:

Environment Variables:
- AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY
- AWS_SESSION_TOKEN (if using temporary credentials)
Shared AWS Config/Credentials Files:
- Config file: ~/.aws/config (Linux/Mac) or %UserProfile%\.aws\config (Windows)
- Credentials file: ~/.aws/credentials (Linux/Mac) or %UserProfile%\.aws\credentials (Windows)
- The AWS_PROFILE environment variable can be used to specify a named profile, otherwise the [default] profile is used.
- Supports both static credentials and SSO sessions
- Example credentials file:
```
# Static credentials
[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY

# SSO profile
[profile sso-profile]
sso_start_url = https://my-sso-portal.awsapps.com/start
sso_region = us-west-2
sso_account_id = 123456789012
sso_role_name = MyRole
region = us-west-2
```
:::tip To set up SSO authentication:
1. Run aws configure sso to configure a new SSO profile
2. Use the profile by setting AWS_PROFILE=sso-profile
3. Run aws sso login --profile sso-profile to start a new SSO session :::
AWS STS Web Identity Token Credentials:
- Used primarily with OpenID Connect (OIDC) and OAuth
- Common in Kubernetes environments using IAM roles for service accounts (IRSA)
ECS Container Credentials:
- Used when running in Amazon ECS containers
- Automatically uses the task's IAM role
- Retrieved from the ECS credential provider endpoint
- Relies on the environment variable AWS_CONTAINER_CREDENTIALS_RELATIVE_URI or AWS_CONTAINER_CREDENTIALS_FULL_URI which are automatically injected by ECS.
AWS EC2 Instance Metadata Service (IMDSv2):
- Used when running on EC2 instances.
- Automatically uses the instance's IAM role.
- Retrieved securely using IMDSv2.

The connector will try each source in order until valid credentials are found. If no valid credentials are found, an authentication error will be returned.

:::note[IAM Permissions] Regardless of the credential source, the IAM role or user must have appropriate DynamoDB permissions (e.g., dynamodb:Scan, dynamodb:Query, dynamodb:DescribeTable) to access the tables. If the Spicepod connects to multiple different AWS services, the permissions should cover all of them. :::

Required IAM Permissions

The IAM role or user needs the following permissions to access DynamoDB tables:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "dynamodb:Scan",
                "dynamodb:Query",
                "dynamodb:DescribeTable"
            ],
            "Resource": [
                "arn:aws:dynamodb:*:*:table/YOUR_TABLE_NAME"
            ]
        }
    ]
}

Permission Details

Permission	Purpose
`dynamodb:Scan`	Required. Allows reading all items from the table
`dynamodb:Query`	Required. Allows reading items from the table using partition key
`dynamodb:DescribeTable`	Required. Allows fetching table metadata and schema information

Example IAM Policies

Minimal Policy (Read-only access to specific table)

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "dynamodb:Scan",
                "dynamodb:Query",
                "dynamodb:DescribeTable"
            ],
            "Resource": "arn:aws:dynamodb:us-west-2:123456789012:table/users"
        }
    ]
}

Access to Multiple Tables

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "dynamodb:Scan",
                "dynamodb:Query",
                "dynamodb:DescribeTable"
            ],
            "Resource": [
                "arn:aws:dynamodb:us-west-2:123456789012:table/users",
                "arn:aws:dynamodb:us-west-2:123456789012:table/orders"
            ]
        }
    ]
}

Access to All Tables in a Region

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "dynamodb:Scan",
                "dynamodb:Query",
                "dynamodb:DescribeTable"
            ],
            "Resource": "arn:aws:dynamodb:us-west-2:123456789012:table/*"
        }
    ]
}

:::warning[Security Considerations]

Avoid using dynamodb:* permissions as it grants more access than necessary.
Consider using more restrictive policies in production environments.
When using IAM roles with EKS, ensure the service account is properly configured with IRSA.

:::

Data Types

The table below shows the DynamoDB data types supported, along with the type mapping to Apache Arrow types in Spice.

DynamoDB Type	Description	Arrow Type	Notes
`Bool`	Boolean	`Boolean`
`S`	String	`Utf8`
`S`	String	`Timestamp(Millisecond)`	Naive timestamp if it matches `time_format` without timezone
`S`	String	`Timestamp(Millisecond, <timezone>)`	Timezone-aware timestamp if it matches `time_format` with timezone
`Ss`	String Set	`List<Utf8>`
`N`	Number	`Int64` \| `Float64`
`Ns`	Number Set	`List<Int64\|Float64>`
`B`	Binary	`Binary`
`Bs`	Binary Set	`List<Binary>`
`L`	List	`List<Utf8>`	DynamoDB arrays can be heterogeneous e.g. `[1, "foo", true]`, Arrow arrays must be homogeneous - use strings to preserve all data
`M`	Map	`Utf8` or Unflattened	Depending on `unnest_depth` value

Time format

Since DynamoDB stores timestamps as strings, Spice supports parsing timestamps using a customizable format. By default, Spice will try to parse timestamps using ISO8601 format, but you can provide a custom format using the time_format parameter.

Once Spice is able to parse a timestamp, it will convert it to a Timestamp(Millisecond) Arrow type, and will use the same format to serialize it back to DynamoDB for filter pushdown.

This parameter uses Go-style time formatting, which uses a reference time of Mon Jan 2 15:04:05 MST 2006.

Format Pattern	Example Value	Description
`2006-01-02T15:04:05.000Z07:00`	`2024-03-15T14:30:00.000Z`	ISO8601 / RFC3339 with milliseconds and timezone (default)
`2006-01-02T15:04:05.999Z07:00`	`2024-03-15T14:30:00.123-07:00`	ISO8601 with variable-length milliseconds and timezone
`2006-01-02T15:04:05`	`2024-03-15T14:30:00`	ISO8601 without timezone (naive timestamp)
`2006-01-02 15:04:05`	`2024-03-15 14:30:00`	Date and time with space separator
`01/02/2006 15:04:05`	`03/15/2024 14:30:00`	US-style date with time
`02/01/2006 15:04:05`	`15/03/2024 14:30:00`	European-style date with time
`Jan 2, 2006 3:04:05 PM`	`Mar 15, 2024 2:30:00 PM`	Human-readable with 12-hour clock
`20060102150405`	`20240315143000`	Compact format (no separators)

Go's format uses specific reference values that must appear exactly as shown:

Component	Reference Value	Alternatives
Year	`2006`	`06` (2-digit)
Month	`01`	`1`, `Jan`, `January`
Day	`02`	`2`
Hour (24h)	`15`	—
Hour (12h)	`03`	`3`
Minute	`04`	`4`
Second	`05`	`5`
AM/PM	`PM`	`pm`
Timezone	`Z07:00`	`-0700`, `MST`
Milliseconds	`.000`	`.999` (trailing zeros trimmed)
Microseconds	`.000000`	`.999999` (trailing zeros trimmed)
Nanoseconds	`.000000000`	`.999999999` (trailing zeros trimmed)

Unnesting

Consider the following document:

{
  "a": 1,
  "b": {
    "x": 2,
    "y": {
      "z": 3
    }
  }
}

Using unnest_depth you can control the unnesting behavior. Here are the examples:

unnest_depth: 0

sql> select * from test_table;
+-----------+---------------------+
| a (Int32) | b (Utf8)            |
+-----------+---------------------+
| 1         | {"x":2,"y":{"z":3}} |
+---+-----------------------------+

unnest_depth: 1

sql> select * from test_table;
+-----------+-------------+------------+
| a (Int32) | b.x (Int32) | b.y (Utf8) |
+-----------+-------------+------------+
| 1         | 2           | {"z":3}    | 
+-----------+-------------+------------+

unnest_depth: 2

sql> select * from test_table;
+-----------+-------------+---------------+
| a (Int32) | b.x (Int32) | b.y.z (Int32) |
+-----------+-------------+---------------+
| 1         | 2           | 3             |
+-----------+-------------+---------------+

JSON Nesting

When working with DynamoDB tables that have many columns, you can consolidate unspecified columns into a single JSON column using the json_object metadata option. This is useful when you only need a few columns as discrete fields and want to bundle the remaining columns into a single JSON structure.

Configuration

To use JSON nesting, define your desired columns explicitly in the columns list and add a "catch-all" column with json_object: "*" metadata. Any columns from the source table that are not explicitly listed will be nested into this JSON column.

datasets:
  - from: dynamodb:my_table
    name: my_table
    params:
      dynamodb_aws_region: us-west-2
    columns:
      - name: PK
      - name: SK
      - name: Baz
      - name: data_json
        metadata:
          json_object: "*"

Example

Given a DynamoDB table with this schema:

Column	Type
PK	String
SK	String
Foo	Map
Bar	List
Baz	String

The configuration above produces:

Column	Type
PK	String
SK	String
Baz	String
data_json	JSON (`{"Foo": <map>, "Bar": <list>}`)

The Foo and Bar columns, which were not explicitly listed, are automatically nested into the data_json column as a JSON object.

Interaction with `unnest_depth`

When both unnest_depth and json_object are specified, the operations are applied in this order:

Unnesting first: Nested structures are flattened according to the unnest_depth value
JSON nesting second: Unspecified columns are then consolidated into the json_object column

Consider this DynamoDB dataset:

+----+------+-------------------+------------------------------------------------------+
| PK | SK   | Baz               | Foo                                                  | 
+----+------+-------------------+------------------------------------------------------+
| 1  | 200  | some_string_value | { "Age" : { "N" : "35" }, "Name" : { "S" : "Joe" } } |
+----+------+-------------------+------------------------------------------------------+

And this configuration

datasets:
  - from: dynamodb:my_table
    name: my_table
    params:
      dynamodb_aws_region: us-west-2
      unnest_depth: 1
    columns:
      - name: PK
      - name: SK
        metadata:
          json_object: "*"

Will produce the following Spice dataset:

+----+-----+---------------------------------------------------------+
| PK | SK  | json_data                                               |
+----+-----+---------------------------------------------------------+
| 1  | 200 | {"Baz":"some_string", "Foo.Age":35.0, "Foo.Name":"Joe"} |
+----+-----+---------------------------------------------------------+

:::warning[Limitations]

The json_object metadata only accepts "*" as its value, which captures all unspecified columns
Only one column can have the json_object metadata. Specifying multiple columns with json_object will result in an error

:::

Examples

Basic Configuration with Environment Credentials

version: v1
kind: Spicepod
name: dynamodb

datasets:
  - from: dynamodb:users
    name: users
    params:
      dynamodb_aws_region: us-west-2
    acceleration:
      enabled: true

Configuration with Explicit Credentials

version: v1
kind: Spicepod
name: dynamodb

datasets:
  - from: dynamodb:users
    name: users
    params:
      dynamodb_aws_region: us-west-2
      dynamodb_aws_auth: key
      dynamodb_aws_access_key_id: ${secrets:aws_access_key_id}
      dynamodb_aws_secret_access_key: ${secrets:aws_secret_access_key}
    acceleration:
      enabled: true

Configuration with Metadata-Only Credentials (ECS/EKS)

version: v1
kind: Spicepod
name: dynamodb

datasets:
  - from: dynamodb:users
    name: users
    params:
      dynamodb_aws_region: us-west-2
      dynamodb_aws_auth: iam_role
      dynamodb_aws_iam_role_source: metadata
    acceleration:
      enabled: true

Configuration with time_format

version: v1
kind: Spicepod
name: dynamodb

datasets:
  - from: dynamodb:users
    name: users
    params:
      dynamodb_aws_region: us-west-2
      time_format: 2006-01-02 15:04:05
    acceleration:
      enabled: true

Querying Nested Structures

DynamoDB supports complex nested JSON structures. These fields can be queried using SQL:

-- Query nested structs
SELECT metadata.registration_ip, metadata.user_agent 
FROM users 
LIMIT 5;

-- Query nested structs in arrays
SELECT address.city
FROM (
    SELECT unnest(addresses) AS address 
    FROM users
)
WHERE address.city = 'San Francisco';

:::warning[Limitations]

The DynamoDB connector will scan the first 10 items to determine the schema of the table. This may miss columns that are not present in the first 10 items.
The DynamoDB connector does not support Decimal type.

:::

Example schema from a users table:

describe users;

+----------------+------------------+-------------+
| column_name    | data_type       | is_nullable |
+----------------+------------------+-------------+
| email          | Utf8            | YES         |
| id             | Int64           | YES         |
| metadata       | Struct          | YES         |
| addresses      | List(Struct)    | YES         |
| preferences    | Struct          | YES         |
| created_at     | Utf8            | YES         |
...
+----------------+------------------+-------------+

Streams

The DynamoDB Data Connector integrates with DynamoDB Streams to enable real-time streaming of table changes. This feature supports both initial table bootstrapping and continuous change data capture (CDC), so Spice can automatically detect and stream inserts, updates, and deletes from DynamoDB tables.

:::warning

Using DynamoDB Streams requires acceleration with refresh_mode: changes.

:::

Basic Configuration

To enable streaming from DynamoDB, enable acceleration and set the refresh_mode to changes in your dataset configuration.

datasets:
  - from: dynamodb:my_table
    name: orders_stream
    acceleration:
      enabled: true
      engine: duckdb
      mode: file
      refresh_mode: changes

Configuration Parameters

Dataset Parameters

ready_lag - Defines the maximum lag threshold before the dataset is reported as "Ready". Once the stream lag falls below this value, queries can be executed against the dataset. Default behavior reports ready immediately after bootstrap completes.
scan_interval - Controls the polling frequency for checking new records in the DynamoDB stream. Lower values provide more real-time updates but increase API calls. Higher values reduce API usage but may introduce additional latency.

Acceleration Parameters

snapshots - Optional. Controls snapshots behavior. Supported values are disabled (default), enabled, create_only, bootstrap_only.
snapshots_trigger - Optional. Determines type of trigger for creating snapshots. Supported values are time_interval (default) and stream_batches.
snapshots_trigger_threshold - Optional. Threshold value for snapshot creation. The format depends on the snapshots_trigger type:
- When snapshots_trigger is stream_batches: a raw integer specifying the number of batches (e.g., 100, 1000).
- When snapshots_trigger is time_interval: an integer with a time unit suffix (e.g., 10m, 30s, 1h).

See Acceleration snapshots for more details.

Metrics

The following Component Metrics are provided for monitoring streaming performance and health:

Metric	Type	Description
`shards_active`	Gauge	Current number of active shards in the stream
`records_consumed_total`	Counter	Total number of records consumed from the stream
`lag_ms`	Gauge	Current lag in milliseconds between stream watermark and the current time
`errors_transient_total`	Counter	Total number of transient errors encountered while polling from the stream

These metrics are not enabled by default, enable them by setting the metrics parameter:

datasets:
- from: dynamodb:user_events
  name: events
  acceleration:
    enabled: true
    refresh_mode: changes
  metrics:
   - name: shards_active
   - name: records_consumed_total
   - name: lag_ms
   - name: errors_transient_total

You can find an example dashboard for DynamoDB Streams in monitoring/grafana-dashboard.json.

Advanced Configuration

For production workloads requiring fine-tuned control over streaming behavior and performance characteristics:

datasets:
   - from: dynamodb:my_table
     name: orders_stream
     params:
        ready_lag: 1s          # Dataset reports as Ready when lag is below 1 second
        scan_interval: 100ms   # Poll for new stream records every 100 milliseconds
     acceleration:
        enabled: true
        engine: duckdb
        mode: file
        refresh_mode: changes
        snapshots: enabled
        snapshots_trigger: stream_batches
        snapshots_trigger_threshold: 5  # Create snapshots every 5 batch updates
     metrics:
     - name: shards_active
     - name: records_consumed_total
     - name: lag_ms
     - name: errors_transient_total

:::warning[Limitations]

DynamoDB Streams connector does not support refresh_sql.

:::

Cookbooks

A cookbook recipe to configure DynamoDB as a data connector in Spice. DynamoDB Data Connector
A cookbook recipe to configure DynamoDB Streams as a data connector in Spice. DynamoDB Streams Data Connector

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Configuration

from

name

params

Authentication

IAM Role Authentication (dynamodb_aws_auth: iam_role)

Key-Based Authentication (dynamodb_aws_auth: key)

Default Credential Chain (auto)

Required IAM Permissions

Permission Details

Example IAM Policies

Minimal Policy (Read-only access to specific table)

Access to Multiple Tables

Access to All Tables in a Region

Data Types

Time format

Unnesting

unnest_depth: 0

unnest_depth: 1

unnest_depth: 2

JSON Nesting

Configuration

Example

Interaction with unnest_depth

Examples

Basic Configuration with Environment Credentials

Configuration with Explicit Credentials

Configuration with Metadata-Only Credentials (ECS/EKS)

Configuration with time_format

Querying Nested Structures

Streams

Basic Configuration

Configuration Parameters

Dataset Parameters

Acceleration Parameters

Metrics

Advanced Configuration

Cookbooks

`from`

`name`

`params`

IAM Role Authentication (`dynamodb_aws_auth: iam_role`)

Key-Based Authentication (`dynamodb_aws_auth: key`)

Default Credential Chain (`auto`)

Interaction with `unnest_depth`