Dsql
AWS LabsOfficialPublished by AWS Labs
- Skill
- Tool integration
- Data and AI
- Apache-2.0
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The dsql skill provides a structured framework for interacting with Amazon Aurora DSQL. It encompasses schema management, migration strategies from MySQL and PostgreSQL, performance diagnostics, and bulk data loading. The skill integrates with MCP tools for direct database operations and provides extensive documentation on IAM authentication, multi-tenant patterns, and transaction management to ensure safe and efficient database operations.
What it does
- Executes SQL queries and DDL operations via MCP tools.
- Provides migration paths and type mapping for MySQL and PostgreSQL to DSQL.
- Offers diagnostic workflows for cluster performance and query plan explainability.
- Facilitates bulk data loading using specialized loaders.
- Enforces best practices for IAM authentication and scoped database roles.
- Validates SQL compatibility and provides linting for DSQL-specific constraints.
When to use it
- When building or migrating applications to Aurora DSQL.
- When performing schema changes or complex DDL migrations.
- When troubleshooting performance issues or query plan inefficiencies.
- When setting up multi-tenant database architectures.
- When bulk loading data into a DSQL cluster.
Advantages
- Ensures adherence to DSQL-specific transaction and concurrency limits.
- Promotes secure access patterns through IAM and scoped roles.
- Provides clear, phased workflows for complex tasks like performance tuning.
- Reduces migration friction with automated linting and type mapping guidance.
- Standardizes diagnostic reporting for query plan analysis.
Usage examples
- “How do I migrate my existing PostgreSQL schema to Aurora DSQL?”
- The agent will guide you through pg-migrations/type-mapping.md and schema-objects.md, providing steps to convert indexes, enums, and data types while ensuring compatibility.
- “My query is running slowly on DSQL, can you help?”
- The agent will initiate Workflow 9 (Query Plan Explainability) to analyze the query plan, check for full scans, and provide a structured diagnostic report.
- “How do I set up a multi-tenant table in DSQL?”
- The agent will provide instructions on using tenant_id in your schema design, enforcing it in WHERE clauses, and using separate transact calls for DDL.
- “What are the transaction limits for DSQL?”
- The agent will consult the limits-and-error-codes.md or awsknowledge tool to provide the exact limits for row modifications, data size, and duration.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/awslabs/dsql/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip dsql.zip -d .agents/skills
Documentation by AWS Labs
Amazon Aurora DSQL Skill
Aurora DSQL is a serverless, PostgreSQL-compatible distributed SQL database. This skill covers direct query execution via MCP tools, schema management, migrations, multi-tenant isolation, IAM auth, and bulk data loading via aurora-dsql-loader.
Reference Files
Load these files as needed for detailed guidance:
Core:
| Reference | When to Load | Contains |
|---|---|---|
| development-guide.md | ALWAYS before schema changes or DB operations | Best practices, DDL rules, transaction limits, foreign key constraints |
| foreign-keys.md | MUST load for foreign key operations or migrations | FK syntax, actions, validation, tenant keys |
| language.md | MUST load for language-specific choices | Driver selection, DSQL Connectors, connection code |
| access-control.md | MUST load for roles, grants, or sensitive data | Scoped role setup, IAM-to-database role mapping |
| troubleshooting.md | SHOULD load for errors or unexpected behavior | OCC and 23503, FK, connections, cluster state |
| limits-and-error-codes.md | SHOULD load before sizing batches, keys or indexes, or on 54000/0A000/54011 | Every limit, rejection and quota with SQLSTATE and exact message |
| dsql-examples.md | Load for implementation examples | Multi-tenant access, batch operations, identity and sequences, connection pooling |
| onboarding.md | User requests "Get started with DSQL" | Interactive step-by-step guide |
| occ-retry-patterns.md | MUST load for OCC retry code or conflict mitigation | Connectors, 40001 retry, non-retryable 23503, FK read conflicts, idempotent design |
MCP:
| Reference | When to Load | Contains |
|---|---|---|
| mcp-setup.md | Always for MCP server guidance | Setup instructions, 2 configuration options |
| mcp-tools.md | For MCP tool syntax and examples | Tool parameters, input validation |
| dsql-lint.md | MUST load before running dsql_lint or processing external SQL | Tool reference, fix statuses, unfixable error resolution |
DDL Migrations:
| Reference | When to Load | Contains |
|---|---|---|
| ddl-migrations/overview.md | MUST load for ALTER TYPE, SET NOT NULL, MODIFY PRIMARY KEY | Direct ALTER coverage and last-resort table recreation |
| ddl-migrations/column-operations.md | DROP COLUMN, ALTER TYPE, SET/DROP NOT NULL/DEFAULT | Column-level migration patterns |
| ddl-migrations/constraint-operations.md | ADD/DROP CONSTRAINT, VALIDATE CONSTRAINT, MODIFY PRIMARY KEY | Constraint and structural changes |
| ddl-migrations/batched-migration.md | Tables exceeding 3,000 rows | Batching patterns, progress tracking |
MySQL Migrations:
| Reference | When to Load | Contains |
|---|---|---|
| mysql-migrations/type-mapping.md | MUST load for MySQL → DSQL migration | Data type mappings, feature alternatives |
| mysql-migrations/ddl-operations.md | Translating MySQL DDL to DSQL | AUTO_INCREMENT, ENUM, SET, FK patterns |
| mysql-migrations/full-example.md | Complete MySQL table migration | End-to-end example with decision summary |
PostgreSQL Migrations:
| Reference | When to Load | Contains |
|---|---|---|
| pg-migrations/type-mapping.md | MUST load for DSQL NUMERIC or PG type questions | C collation rules, NUMERIC(p,s), JSON/JSONB |
| pg-migrations/index-conversion.md | MUST load for any index conversion or index support question | GIN/GiST/BRIN → btree, operator class removal, partial + expression indexes, sort order |
| pg-migrations/schema-objects.md | MUST load for ENUM, materialized views, extensions, multi-schema, CREATE FUNCTION | ENUM → CHECK, views, role/IAM mapping, LANGUAGE sql functions |
| pg-migrations/multi-region.md | Multi-region, active-active, or HA questions | Architecture, geographic partitioning |
ORM Guides:
| Reference | When to Load | Contains |
|---|---|---|
| orm-guides/overview.md | Migrating an ORM or using ORM locking with DSQL | Adapter names, locking, and key gotchas for Django/EF Core/Hibernate/Rails/SQLAlchemy |
Data Loading:
| Reference | When to Load | Contains |
|---|---|---|
| data-loading.md | Planning or running bulk loads with aurora-dsql-loader | Fresh-vs-warm partitions, resume/retry, --on-conflict semantics, throughput diagnostics |
System Diagnostics:
| Reference | When to Load | Contains |
|---|---|---|
| system-diagnostics/workflow.md | MUST load at Workflow 12 entry — cluster performance diagnostics | Prerequisites, 5 diagnostic phases, temporal comparison, handoff |
| system-diagnostics/wait-events.md | ALWAYS load when interpreting AAS results | Canonical DSQL wait event descriptions and investigation guidance |
| system-diagnostics/promql-patterns.md | Load when constructing PromQL queries | Reusable query templates for AAS breakdown, top-SQL, temporal compare |
Query Plan Explainability:
| Reference | When to Load | Contains |
|---|---|---|
| query-plan/workflow.md | MUST load at Workflow 9 entry — gates all other files | Trigger criteria, context disambiguation, routing, phased workflow |
| query-plan/plan-interpretation.md | MUST load at Workflow 9 Phase 0 | DSQL node types, Node Duration math, estimation-error bands |
| query-plan/catalog-queries.md | MUST load at Workflow 9 Phase 0 | pg_class/pg_stats/pg_indexes SQL, correlated-predicate verification |
| query-plan/guc-experiments.md | MUST load at Workflow 9 Phase 0 | GUC experiment procedures, 30-second skip protocol |
| query-plan/report-format.md | MUST load at Workflow 9 Phase 0 | Required report structure, element checklist, support request template |
| query-plan/query-rewrites-generic.md | SHOULD load at Phase 0; sub-files on-demand | Index of 10 generic rewrite patterns |
| query-plan/query-rewrites-dsql-specific.md | SHOULD load at Phase 0; sub-files on-demand | Index of DSQL-specific rewrite patterns |
Choosing How to Connect: MCP vs CLI/psql
The aurora-dsql MCP server binds a single cluster at startup (--cluster_endpoint), so
using it for another cluster means editing .mcp.json and restarting the session.
Use the
aurora-dsqlMCP tools (readonly_query,transact,get_schema) ONLY when the server already targets the cluster you need.Otherwise — unconfigured, disabled, or bound to a different cluster — do NOT reconfigure it. Use the CLI +
psqlpath instead:scripts/psql-connect.sh<cluster-id> --region <region> --command "SELECT ..."(mints an IAM token and runs viapsql).If you cannot confirm which cluster the MCP targets, confirm first or use the CLI/psql path — running against the wrong cluster is worse than the check.
The doc-only MCP tools (dsql_lint, dsql_*_documentation, dsql_recommend) need no cluster.
The CloudWatch MCP (Workflow 12) takes region/cluster_id per call, so one running server can
query clusters in any PromQL-enabled region (pass each cluster's region on the call). Details:
connectivity-tools.md.
MCP Tools Available
The aurora-dsql MCP server provides these tools:
Database Operations:
readonly_query - Execute SELECT queries (returns list of dicts)
transact - Execute DDL/DML statements in transaction (takes list of SQL statements)
get_schema - Get table structure for a specific table
SQL Validation:
dsql_lint - Validate SQL for DSQL compatibility and optionally auto-fix issues. Use before executing externally-sourced SQL.
Documentation & Knowledge:
dsql_search_documentation - Search Aurora DSQL documentation
dsql_read_documentation - Read specific documentation pages
dsql_recommend - Get DSQL best practice recommendations
Note: There is no list_tables tool. Use readonly_query with information_schema.
See mcp-setup.md for detailed setup instructions. See mcp-tools.md for detailed usage and examples.
AWS Knowledge MCP (awsknowledge)
Consult for verifying DSQL service limits before advising users. The numeric limits below are defaults that may change — when a user's decision depends on an exact limit, verify it first:
| Limit | Default | Verify query |
|---|---|---|
| Max row modifications per transaction | 3,000 | aurora dsql transaction limits |
| Max data size per transaction | 10 MiB | aurora dsql transaction limits |
| Max transaction duration | 5 minutes | aurora dsql transaction limits |
| Max connections per cluster | 10,000 | aurora dsql connection limits |
| Auth token expiry | 15 minutes | aurora dsql authentication token |
| Max connection duration | 60 minutes | aurora dsql connection limits |
| Max indexes per table | 24 incl. PK | aurora dsql index limits |
| Max columns per index | 8 | aurora dsql index limits |
| IDENTITY/SEQUENCE CACHE values | 1 or >= 65536 | aurora dsql sequence cache |
| Supported column data types | See docs | aurora dsql supported data types |
When to verify: Before recommending batch sizes, connection pool settings, or schema designs where hitting a limit would cause failures; any time the exact number can affect user decision. For the full limit set with each SQLSTATE and its exact error message, see limits-and-error-codes.md; where it marks a value observed and the docs differ, use the observed value.
Fallback: If awsknowledge is unavailable, use the defaults above and flag that limits should be verified against DSQL documentation.
CLI Scripts Available
Bash scripts in scripts/ for cluster management (create, delete, list, cluster info), psql connection, and bulk data loading from local/s3 csv/tsv/parquet files. See scripts/README.md for usage and hook configuration.
Quick Start
Pick a connection path: confirm the
aurora-dsqlMCP targets your cluster; if not, use the CLI/psqlpath instead — see Choosing How to Connect. The steps below name MCP tools; the equivalent SQL runs the same way throughpsql-connect.sh --command "...".Explore: Use
readonly_querywithinformation_schemato list tables. Useget_schemafor table structure.Query: Use
readonly_queryfor SELECT queries. MUST includetenant_idin WHERE for multi-tenant apps. MUST build SQL withsafe_query.build().Schema changes: Use
transactwith one DDL per transaction. MUST batch DML under 3,000 rows. MUST useCREATE INDEX ASYNCin a separate call. Usedsql_lintto validate first.Bulk load data: Use
aurora-dsql-loaderfor CSV/TSV/Parquet. Load data-loading.md for details. Use--dry-runfirst.
Performance Routing
When the user reports a performance problem, use this table to select the correct workflow:
| User signal | Route to |
|---|---|
| General performance complaint, "cluster is slow", "something changed", latency regression, no specific query identified | Workflow 12 (System Diagnostics) — observe via CloudWatch first |
| Specific query or query_id to investigate, "explain this plan", "why is this query slow" | Workflow 9 (Query Plan Explainability) — direct EXPLAIN analysis |
| OCC conflicts, commit errors, retry storms | Workflow 12 (System Diagnostics) — confirm via CW metrics before investigating |
| Cost optimization, "where is compute time spent" | Workflow 12 (System Diagnostics) — identify top contributors first |
Rule: When in doubt, start with Workflow 12. It identifies specific queries to investigate and routes to Workflow 9 with context.
Common Workflows
Workflow 1: Create Multi-Tenant Schema
Create tenant-owned tables with
tenant_idusing separatetransactcallsUse composite tenant FKs for tenant-owned parents and ordinary FKs for shared parents
Create tenant and query-pattern indexes with separate
CREATE INDEX ASYNCcallsVerify with
get_schema
MUST issue each DDL in its own transact call:
transact(["CREATE TABLE ..."])MUST serialize arrays into a single-column representation — DSQL has no array column type; PREFER
JSONB(operators work directly); MAY useTEXTwhen the column is opaque to the database; ASK the user. ForJSONBarrays, expand at query time withjsonb_array_elements_text(data)
Workflow 2: Safe Data Migration
MUST validate every DDL with dsql_lint(fix=true) before executing. DML does not require linting.
Validate DDL with
dsql_lint(sql=..., fix=true)— handle diagnostics per dsql-lint.mdExecute the reviewed
fixed_sqlwhen present, otherwise the reviewed source statementAdd column in its own
transactcallPopulate existing rows with UPDATE (batched under 3,000 rows)
Verify with readonly_query COUNT
Create an index if needed: validate then execute the reviewed DDL in its own
transactcall
MUST issue each
ALTER TABLEin its owntransactcall — DSQL rejects multi-DDL transactions withmultiple ddl statements not supported in a transactionMUST add column with only name and type; apply DEFAULT via separate UPDATE
MUST batch updates under 3,000 rows in separate transact calls
Recovery: Resume failed batches by filtering WHERE new_column IS NULL.
Workflow 3: Bulk Data Loading
Use aurora-dsql-loader for CSV, TSV, or Parquet loads. MUST load data-loading.md before advising on throughput or diagnosing slow loads.
Validate with
--dry-runfirstRun with
--manifest-diron persistent storage (not/tmp— tmpfs on AL2023, lost on crash) and--headerif file has a header rowOn failure: resume with
--resume-job-id; for duplicates use--on-conflict do-nothingFor large tables: create secondary indexes after load using
CREATE INDEX ASYNC
Workflow 4: Foreign Key Constraints
MUST load and follow foreign-keys.md before creating, altering, dropping, or migrating foreign keys.
Workflow 5: Query with Tenant Isolation
MUST authorize the caller against the tenant — format validation does not establish authorization
MUST build SQL with
safe_query.build()— useallow()/regex()for values (emits'v'),ident()for table/column names (emits"v"). See input-validation.mdMUST include
tenant_idin the WHERE clause; reject cross-tenant access at the application layer
Workflow 6: Set Up Scoped Database Roles
MUST load access-control.md for role setup, IAM mapping, and schema permissions.
Workflow 7: Table Recreation DDL Migration
For ALTER COLUMN TYPE, SET NOT NULL, or MODIFY PRIMARY KEY, MUST
load ddl-migrations/overview.md. Use a direct ALTER form
when supported; otherwise, present a user-approved table-recreation plan.
Workflow 8: Validate and Migrate to DSQL
MUST load dsql-lint.md before running dsql_lint. Run dsql_lint(sql=source_sql, fix=true) to validate and auto-convert. For MySQL-origin SQL, MUST cross-check against mysql-migrations/type-mapping.md even when lint returns clean. On parse_error, fall back to manual conversion then re-lint.
Workflow 9: Query Plan Explainability
Explains why the DSQL optimizer chose a particular plan. Triggered by slow queries, high DPU, unexpected Full Scans, or plans the user doesn't understand. REQUIRES a structured Markdown diagnostic report as the deliverable.
MUST load query-plan/workflow.md at entry — it defines trigger criteria, context disambiguation, routing, and the full phased workflow (Phase 0–4). Workflow.md specifies which reference files to load at each phase.
Safety. Plan capture uses readonly_query exclusively. Rewrite DML to SELECT for plan capture. MUST NOT use transact --allow-writes for plan capture.
Workflow 10: Full PostgreSQL → DSQL Schema Migration
MUST load pg-migrations/type-mapping.md, pg-migrations/index-conversion.md, pg-migrations/schema-objects.md, and foreign-keys.md. Run dsql_lint(fix=true) first for mechanical fixes, preserve foreign-key relationships, translate unsupported source syntax or options, then apply semantic conversions from the pg-migrations references for unfixable diagnostics and patterns the linter cannot handle. Re-lint the final output before deploying.
Workflow 11: ORM Migration and Locking (Django/EF Core/Hibernate/Rails/SQLAlchemy)
Load orm-guides/overview.md for adapter names, locking guidance, and framework-specific gotchas.
Workflow 12: System Diagnostics (CloudWatch AAS)
Diagnose cluster performance by querying db.active_sessions.avg via PromQL. Detects temporal anomalies in wait event distribution, identifies regressed queries, and routes to Workflow 9 for per-query investigation.
Requires: CloudWatch MCP server (awslabs.cloudwatch-mcp-server) enabled and configured with PromQL access in the same region as the cluster — see mcp/mcp-setup.md for enabling it, region requirements, and the session restart needed for its tools to register.
MUST load system-diagnostics/workflow.md at entry — it defines prerequisites, 5 diagnostic phases, temporal baselines, and the routing to Workflow 9 for identified queries.
Error Scenarios
awsknowledgereturns no results: Use the default limits in the table above and note that limits should be verified against DSQL documentation.dsql_lintunavailable or timing out: See the Error Handling section of dsql-lint.md. Do not silently skip validation — inform the user and require explicit confirmation before proceeding with manual rules from development-guide.md.OCC serialization error (
40001): Retry with backoff, and keep(OC001)in the loop too — see occ-retry-patterns.md.Foreign key violation (
23503): Correct the relationship or referential action; MUST NOT send it through the40001retry loop — see troubleshooting.md.Transaction exceeds limits: Split batches under 3,000 rows and 10 MiB; size is checked at
COMMIT— see limits-and-error-codes.md to size them and batched-migration.md for the pattern.Token expiration mid-operation: Generate a fresh IAM token — see authentication-guide.md. See troubleshooting.md for other issues.
Additional Resources
Files
- ATTRIBUTION.mdAdded by AutoGineer868 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer89 B
- SKILL.md27.9 KiB
- mcp/mcp-setup.md6.7 KiB
- mcp/mcp-tools.md2.0 KiB
- mcp/platforms/claude-code.md3.6 KiB
- mcp/platforms/codex.md1.6 KiB
- mcp/platforms/gemini.md2.1 KiB
- mcp/platforms/kiro.md2.8 KiB
- mcp/tools/database-tools.md4.6 KiB
- mcp/tools/documentation-tools.md1.3 KiB
- mcp/tools/input-validation.md3.3 KiB
- mcp/tools/safe_query.pyScript10.4 KiB
- mcp/tools/workflow-patterns.md3.1 KiB
- references/access-control.md5.0 KiB
- references/auth/authentication-guide.md4.6 KiB
- references/auth/connectivity-tools.md8.7 KiB
- references/auth/scaling-guide.md3.9 KiB
- references/data-loading.md6.0 KiB
- references/ddl-migrations/batched-migration.md2.5 KiB
- references/ddl-migrations/column-operations.md5.2 KiB
- references/ddl-migrations/constraint-operations.md6.7 KiB
- references/ddl-migrations/overview.md4.8 KiB
- references/development-guide.md9.6 KiB
- references/dsql-examples.md1.5 KiB
- references/dsql-lint.md10.8 KiB
- references/examples/connection.md2.5 KiB
- references/examples/data-operations.md2.9 KiB
- references/examples/migrations.md1.6 KiB
- references/examples/patterns.md5.5 KiB
- references/examples/schema.md1.6 KiB
- references/foreign-keys.md6.0 KiB
- references/language.md8.6 KiB
- references/limits-and-error-codes.md19.2 KiB
- references/mysql-migrations/ddl-auto-increment.md4.3 KiB
- references/mysql-migrations/ddl-batching.md1.0 KiB
- references/mysql-migrations/ddl-column-changes.md1.3 KiB
- references/mysql-migrations/ddl-constraints.md782 B
- references/mysql-migrations/ddl-operations.md1.5 KiB
- references/mysql-migrations/ddl-structural.md3.7 KiB
- references/mysql-migrations/ddl-type-alternatives.md4.5 KiB
- references/mysql-migrations/full-example.md7.3 KiB
- references/mysql-migrations/type-mapping.md14.3 KiB
- references/occ-retry-patterns.md9.6 KiB
- references/onboarding.md13.8 KiB
- references/orm-guides/overview.md10.9 KiB
- references/pg-migrations/index-conversion.md15.7 KiB
- references/pg-migrations/multi-region.md2.9 KiB
- references/pg-migrations/schema-objects.md15.0 KiB
- references/pg-migrations/type-mapping.md5.3 KiB
- references/query-plan/catalog-queries.md8.0 KiB
- references/query-plan/guc-experiments.md7.5 KiB
- references/query-plan/plan-interpretation.md15.0 KiB
- references/query-plan/query-rewrites-dsql-specific.md900 B
- references/query-plan/query-rewrites-generic.md1.9 KiB
- references/query-plan/query-rewrites/cte-late-materialization.md1.4 KiB
- references/query-plan/query-rewrites/flatten-union-all.md946 B
- references/query-plan/query-rewrites/left-join-to-inner.md794 B
- references/query-plan/query-rewrites/not-in-to-not-exists.md1.4 KiB
- references/query-plan/query-rewrites/or-to-in.md889 B
- references/query-plan/query-rewrites/propagate-filter.md1.0 KiB
- references/query-plan/query-rewrites/push-computation-to-constant.md1.0 KiB
- references/query-plan/query-rewrites/push-group-by-into-subquery.md1.6 KiB
- references/query-plan/query-rewrites/reltuples-estimate.md1.2 KiB
- references/query-plan/query-rewrites/split-large-joins.md2.2 KiB
- references/query-plan/query-rewrites/subquery-unnesting-correlated.md1.6 KiB
- references/query-plan/query-rewrites/subquery-unnesting-scalar.md1.4 KiB
- references/query-plan/query-rewrites/subquery-unnesting-uncorrelated.md1.4 KiB
- references/query-plan/report-format.md10.9 KiB
- references/query-plan/workflow.md9.4 KiB
- references/system-diagnostics/promql-patterns.md8.6 KiB
- references/system-diagnostics/wait-events.md13.7 KiB
- references/system-diagnostics/workflow.md19.4 KiB
- references/troubleshooting.md11.7 KiB
references/pg-migrations/schema-objects.md
Schema Object Conversion for DSQL
Conversion patterns for PostgreSQL schema objects that dsql_lint either doesn't handle
or flags as unfixable. Covers ENUM types, materialized views, extensions, roles/grants,
multi-schema flattening, and other structural conversions.
Sources:
Table of Contents
ENUM Types → CHECK Constraints
Composite Types → JSONB or Separate Columns
Materialized Views → Regular Views
Temporary Tables → Regular Tables or CTEs
Partitioned Tables → Flat Tables
Inherited Tables → Flat (Columns Merged)
Extensions → Alternatives
Roles/GRANT → IAM Mapping
Multi-Schema Handling
UNLOGGED Tables → Regular Tables
CREATE DOMAIN → Preserved
GENERATED ALWAYS AS STORED → Preserved
WITH (storage parameters) → Removed
CREATE FUNCTION → LANGUAGE sql Only
Conversion Checklist
ENUM Types → CHECK Constraints
PostgreSQL ENUM types convert to varchar + CHECK constraint in DSQL.
Before (PostgreSQL):
CREATE TYPE ticket_status AS ENUM ('open', 'in_progress', 'resolved', 'closed');
CREATE TYPE priority_level AS ENUM ('low', 'medium', 'high', 'critical');
CREATE TABLE tickets (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
status ticket_status NOT NULL DEFAULT 'open',
priority priority_level NOT NULL DEFAULT 'medium'
);After (DSQL):
CREATE TABLE tickets (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
status varchar(20) NOT NULL DEFAULT 'open'
CHECK (status IN ('open', 'in_progress', 'resolved', 'closed')),
priority varchar(20) NOT NULL DEFAULT 'medium'
CHECK (priority IN ('low', 'medium', 'high', 'critical'))
);Important: Define CHECK constraints inline for new tables. For existing tables, use
ALTER TABLE ... ADD CONSTRAINT ... CHECK (...) NOT VALID, then validate asynchronously.
Conversion steps:
Find all
CREATE TYPE ... AS ENUMstatementsFind all columns using those types
Replace the column type with
varchar(N)where N fits the longest valueAdd
CHECK (column IN ('val1', 'val2', ...))inline in CREATE TABLEDrop the
CREATE TYPEstatement entirely
Composite Types → JSONB or Separate Columns
-- PostgreSQL
CREATE TYPE address AS (street text, city text, state text, zip text);
CREATE TABLE customers (id uuid PRIMARY KEY, home_address address);
-- DSQL Option 1: JSONB column (flexible)
CREATE TABLE customers (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
home_address jsonb -- {"street":"...","city":"...","state":"...","zip":"..."}
);
-- Query: SELECT home_address->>'city' FROM customers;
-- DSQL Option 2: Separate columns (indexable)
CREATE TABLE customers (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
home_street text,
home_city text,
home_state text,
home_zip text
);
CREATE INDEX ASYNC idx_customers_city ON customers (home_city);Decision: Use JSONB if you rarely query individual fields. Use separate columns if you need to index or filter on specific fields.
Materialized Views → Regular Views
-- PostgreSQL
CREATE MATERIALIZED VIEW monthly_stats AS
SELECT date_trunc('month', created_at) AS month, COUNT(*) AS total
FROM orders GROUP BY 1;
-- Refreshed with: REFRESH MATERIALIZED VIEW monthly_stats;
-- DSQL: Regular view (always up-to-date, no refresh needed)
CREATE VIEW monthly_stats AS
SELECT date_trunc('month', created_at) AS month, COUNT(*) AS total
FROM orders GROUP BY 1;Trade-off: Regular views compute on every query (no caching). For expensive aggregations:
Use application-layer caching (Redis, ElastiCache)
Pre-compute into a summary table updated by application logic
Accept the query cost if the dataset is small
Temporary Tables → Regular Tables or CTEs
-- PostgreSQL
CREATE TEMP TABLE staging_data (id serial, payload jsonb);
INSERT INTO staging_data SELECT ...;
-- Used within a session, auto-dropped on disconnect
-- DSQL Option 1: CTE (for single-query use)
WITH staging_data AS (
SELECT id, payload FROM source_table WHERE ...
)
SELECT * FROM staging_data WHERE ...;
-- DSQL Option 2: Regular table with prefix (for multi-statement use)
CREATE TABLE _tmp_staging_data (
id bigint GENERATED BY DEFAULT AS IDENTITY (CACHE 1),
session_id uuid NOT NULL, -- track which session owns the data
payload jsonb
);
-- Clean up: DELETE FROM _tmp_staging_data WHERE session_id = $1;Partitioned Tables → Flat Tables
-- PostgreSQL
CREATE TABLE events (
id uuid, tenant_id uuid, created_at timestamptz, data jsonb
) PARTITION BY RANGE (created_at);
CREATE TABLE events_2024_q1 PARTITION OF events FOR VALUES FROM ('2024-01-01') TO ('2024-04-01');
-- DSQL: Flat table (DSQL handles distribution internally via PK-ordered storage)
CREATE TABLE events (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
tenant_id uuid NOT NULL,
created_at timestamptz NOT NULL DEFAULT now(),
data jsonb
);
-- No ASC/DESC on index keys — DSQL rejects sort direction with
-- 0A000: specifying sort order not supported for index keys.
-- A backward scan still serves a uniformly-descending ORDER BY on these keys.
CREATE INDEX ASYNC idx_events_tenant_created ON events (tenant_id, created_at);Note: DSQL's PK-ordered storage and distributed architecture handle data distribution automatically. Manual partitioning is not needed and not supported.
Inherited Tables → Flat (Columns Merged)
-- PostgreSQL
CREATE TABLE base_entity (id uuid PRIMARY KEY, created_at timestamptz, updated_at timestamptz);
CREATE TABLE users (email text, name text) INHERITS (base_entity);
CREATE TABLE products (sku text, price numeric) INHERITS (base_entity);
-- DSQL: Merge inherited columns into each child table
CREATE TABLE users (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
created_at timestamptz DEFAULT now(),
updated_at timestamptz DEFAULT now(),
email text,
name text
);
CREATE TABLE products (
id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
created_at timestamptz DEFAULT now(),
updated_at timestamptz DEFAULT now(),
sku text,
price numeric(10,2)
);Extensions → Alternatives
| PostgreSQL Extension | DSQL Alternative | Notes |
|---|---|---|
| uuid-ossp | gen_random_uuid() | Built-in, no extension needed |
| pgcrypto | gen_random_uuid() | For other crypto, use application layer |
| pg_trgm | None | Use OpenSearch for fuzzy search |
| postgis | None | Store coords as numeric columns or geohash text |
| hstore | jsonb type | Use jsonb column instead |
| citext | varchar + lower() | Case-insensitive via application queries |
| pg_stat_statements | None | DSQL has own monitoring |
| btree_gin / btree_gist | None | Use btree indexes directly |
| tablefunc (crosstab) | None | Pivot in application layer |
| ltree | text + application logic | Hierarchical queries in app |
Conversion:
-- PostgreSQL
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
SELECT uuid_generate_v4();
-- DSQL: Remove extension, replace function
-- DROP the CREATE EXTENSION statement
SELECT gen_random_uuid(); -- built-in replacementRoles/GRANT → IAM Mapping
DSQL supports CREATE ROLE and GRANT/REVOKE but they're linked to IAM.
-- PostgreSQL
CREATE ROLE app_reader WITH LOGIN PASSWORD 'secret';
GRANT SELECT ON ALL TABLES IN SCHEMA public TO app_reader;
-- DSQL: Role creation works, but auth is IAM-based (no passwords)
CREATE ROLE app_reader;
GRANT USAGE ON SCHEMA public TO app_reader;
GRANT SELECT ON ALL TABLES IN SCHEMA public TO app_reader;
-- Authentication: IAM role mapped to database role via dsql:DbConnect policyKey differences:
Authentication is always IAM token-based (no
WITH LOGIN PASSWORD)Use explicit GRANT per object (no
ALTER DEFAULT PRIVILEGES)Implement Row-Level Security (RLS) in the application layer
Remove
SECURITY DEFINERfrom function definitions — after removal the function executes as the caller's role. Audit table-level GRANTs to every role that calls the function: missing GRANTs causepermission deniedat runtime where the definer previously succeeded. Where the function gated row visibility (e.g., callers had no direct table GRANT and relied on the function's filter), removingSECURITY DEFINERrequires re-granting access — typically via a view + RLS-in-application, since DSQL has noSECURITY DEFINERsubstitute.Admin role is predefined and immutable
IAM mapping:
{
"Effect": "Allow",
"Action": "dsql:DbConnect",
"Resource": "arn:aws:dsql:us-east-1:123456789012:cluster/cluster-id",
"Condition": {
"StringEquals": {
"dsql:DbUser": "app_reader"
}
}
}Multi-Schema Handling
DSQL supports up to 10 schemas per database (DSQL service limit).
≤10 Schemas: Direct Migration
-- PostgreSQL schemas migrate directly
CREATE SCHEMA billing;
GRANT USAGE ON SCHEMA billing TO app_role;
CREATE TABLE billing.invoices (id uuid PRIMARY KEY, amount numeric(10,2));
CREATE SCHEMA support;
GRANT USAGE ON SCHEMA support TO app_role;
CREATE TABLE support.tickets (id uuid PRIMARY KEY, title text);>10 Schemas: Consolidate with Prefixes
-- PostgreSQL has 15 schemas — must consolidate to ≤10
-- Strategy: merge least-used schemas into 'public' with table name prefixes
-- Schema 'analytics' (overflow) → prefix tables
CREATE TABLE public.analytics_reports (id uuid PRIMARY KEY, ...);
CREATE TABLE public.analytics_dashboards (id uuid PRIMARY KEY, ...);
-- Update all references in application code:
-- FROM: analytics.reports → TO: public.analytics_reportssearch_path Behavior
-- DSQL supports search_path
SET search_path TO billing, public;
SELECT * FROM invoices; -- resolves to billing.invoices
-- NOTE: After schema DDL, refresh connection for immediate visibilityUNLOGGED Tables → Regular Tables
-- PostgreSQL: UNLOGGED for performance (data lost on crash)
CREATE UNLOGGED TABLE session_cache (key text PRIMARY KEY, value jsonb);
-- DSQL: All tables are durable. Remove UNLOGGED keyword.
CREATE TABLE session_cache (
key text PRIMARY KEY,
value jsonb
);
-- If you need non-durable caching, use ElastiCache/Redis instead.CREATE DOMAIN → Preserved
DSQL supports CREATE DOMAIN:
-- PostgreSQL
CREATE DOMAIN email_address AS varchar(255) CHECK (VALUE ~ '^[^@]+@[^@]+\.[^@]+$');
-- DSQL: Works as-is (DOMAIN is supported)
CREATE DOMAIN email_address AS varchar(255)
CHECK (VALUE ~ '^[^@]+@[^@]+\.[^@]+$');GENERATED ALWAYS AS STORED → Preserved
DSQL supports computed columns in CREATE TABLE only —
ALTER TABLE ... ADD COLUMN ... GENERATED is rejected with
ERROR: 0A000: ALTER TABLE ADD COLUMN with constraint not supported:
-- PostgreSQL
CREATE TABLE products (
price numeric(10,2),
tax_rate numeric(4,2),
total numeric(10,2) GENERATED ALWAYS AS (price * (1 + tax_rate)) STORED
);
-- DSQL: Works as-is
CREATE TABLE products (
price numeric(10,2),
tax_rate numeric(4,2),
total numeric(10,2) GENERATED ALWAYS AS (price * (1 + tax_rate)) STORED
);WITH (storage parameters) → Removed
-- PostgreSQL
CREATE TABLE hot_data (id uuid PRIMARY KEY, data jsonb) WITH (fillfactor = 70);
ALTER TABLE hot_data SET (autovacuum_vacuum_threshold = 100);
-- DSQL: Remove all storage parameters. DSQL manages storage automatically.
CREATE TABLE hot_data (id uuid PRIMARY KEY DEFAULT gen_random_uuid(), data jsonb);
-- No VACUUM needed — DSQL handles automatically.CREATE FUNCTION → LANGUAGE sql Only
DSQL supports SQL-language functions. LANGUAGE plpgsql and other procedural languages are
rejected, as is CREATE PROCEDURE.
-- DSQL: supported — all three body forms
CREATE FUNCTION add_quoted(a integer, b integer) RETURNS integer
AS 'SELECT a + b;' LANGUAGE sql IMMUTABLE;
CREATE FUNCTION add_return(a integer, b integer) RETURNS integer
LANGUAGE sql IMMUTABLE RETURN a + b;
CREATE FUNCTION employees_in_dept(dept_id integer) RETURNS TABLE (id integer, name text)
LANGUAGE sql STABLE
BEGIN ATOMIC
SELECT id, name FROM employees WHERE department_id = dept_id;
END;
-- DSQL: rejected — move the logic to the application layer
CREATE FUNCTION bump() RETURNS trigger AS $$ BEGIN RETURN NEW; END; $$ LANGUAGE plpgsql;
-- ERROR: 0A000: CREATE FUNCTION with language plpgsql not supported
CREATE PROCEDURE do_work() LANGUAGE sql AS $$ SELECT 1; $$;
-- ERROR: PROCEDURE is not supporteddsql_lint cannot parse BEGIN ATOMIC bodies — it returns parse_error and a fixed_sql split at
the ; inside the body, so discard fixed_sql and execute the definition as written.
Mark functions used in index expressions IMMUTABLE — see index-conversion.md.
Conversion Checklist
[ ] Find all
CREATE TYPE ... AS ENUM→ convert to CHECK constraints[ ] Find all
CREATE TYPE ... AS (composite)→ convert to jsonb or separate columns[ ] Find all
CREATE MATERIALIZED VIEW→ convert to regular VIEW[ ] Find all
CREATE TEMP TABLE→ convert to CTE or regular table with tmp prefix[ ] Find all
PARTITION BY→ remove (DSQL handles distribution)[ ] Find all
INHERITS→ merge columns into child tables[ ] Find all
CREATE EXTENSION→ remove and use alternatives[ ] Find all
UNLOGGED→ remove keyword[ ] Find all
WITH (fillfactor=...)→ remove storage parameters[ ] Find all
CREATE FUNCTION→ keep SQL-language bodies (AS,RETURN,BEGIN ATOMIC), else move to application layer[ ] Audit roles/grants → remove passwords, map to IAM
[ ] Count schemas → consolidate if >10
[ ] Run
dsql_lint(fix=true)— auto-strips COLLATE clauses from all string columns
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an MCP server, Needs Python, Needs Node.js
Security
What our scanner noticed· Low risk
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Attribution and licence
- Published by
- AWS Labs
- Publisher
- AWS Labs (Official)
- Source
- awslabs/agent-plugins · plugins/databases-on-aws/skills/dsql · commit fbefb37
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download dsql.zip