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Dsql

AWS LabsOfficialPublished by AWS Labs

  • Skill
  • Tool integration
  • Data and AI
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key constraints, OCC retry patterns, ORM migration (Django/EF Core/Hibernate/Rails/SQLAlchemy), DDL operations, query plan explainability, system diagnostics via CloudWatch AAS, SQL compatibility validation, and bulk data loading. Load before answering DSQL limit or error-code questions; it has limits docs omit. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader, DSQL slow, DSQL performance, DSQL wait events, DSQL AAS.
— the description by AWS Labs

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

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/awslabs/dsql/download
  2. Unzip 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:
ReferenceWhen to LoadContains
development-guide.mdALWAYS before schema changes or DB operationsBest practices, DDL rules, transaction limits, foreign key constraints
foreign-keys.mdMUST load for foreign key operations or migrationsFK syntax, actions, validation, tenant keys
language.mdMUST load for language-specific choicesDriver selection, DSQL Connectors, connection code
access-control.mdMUST load for roles, grants, or sensitive dataScoped role setup, IAM-to-database role mapping
troubleshooting.mdSHOULD load for errors or unexpected behaviorOCC and 23503, FK, connections, cluster state
limits-and-error-codes.mdSHOULD load before sizing batches, keys or indexes, or on 54000/0A000/54011Every limit, rejection and quota with SQLSTATE and exact message
dsql-examples.mdLoad for implementation examplesMulti-tenant access, batch operations, identity and sequences, connection pooling
onboarding.mdUser requests "Get started with DSQL"Interactive step-by-step guide
occ-retry-patterns.mdMUST load for OCC retry code or conflict mitigationConnectors, 40001 retry, non-retryable 23503, FK read conflicts, idempotent design
MCP:
ReferenceWhen to LoadContains
mcp-setup.mdAlways for MCP server guidanceSetup instructions, 2 configuration options
mcp-tools.mdFor MCP tool syntax and examplesTool parameters, input validation
dsql-lint.mdMUST load before running dsql_lint or processing external SQLTool reference, fix statuses, unfixable error resolution
DDL Migrations:
ReferenceWhen to LoadContains
ddl-migrations/overview.mdMUST load for ALTER TYPE, SET NOT NULL, MODIFY PRIMARY KEYDirect ALTER coverage and last-resort table recreation
ddl-migrations/column-operations.mdDROP COLUMN, ALTER TYPE, SET/DROP NOT NULL/DEFAULTColumn-level migration patterns
ddl-migrations/constraint-operations.mdADD/DROP CONSTRAINT, VALIDATE CONSTRAINT, MODIFY PRIMARY KEYConstraint and structural changes
ddl-migrations/batched-migration.mdTables exceeding 3,000 rowsBatching patterns, progress tracking
MySQL Migrations:
ReferenceWhen to LoadContains
mysql-migrations/type-mapping.mdMUST load for MySQL → DSQL migrationData type mappings, feature alternatives
mysql-migrations/ddl-operations.mdTranslating MySQL DDL to DSQLAUTO_INCREMENT, ENUM, SET, FK patterns
mysql-migrations/full-example.mdComplete MySQL table migrationEnd-to-end example with decision summary
PostgreSQL Migrations:
ReferenceWhen to LoadContains
pg-migrations/type-mapping.mdMUST load for DSQL NUMERIC or PG type questionsC collation rules, NUMERIC(p,s), JSON/JSONB
pg-migrations/index-conversion.mdMUST load for any index conversion or index support questionGIN/GiST/BRIN → btree, operator class removal, partial + expression indexes, sort order
pg-migrations/schema-objects.mdMUST load for ENUM, materialized views, extensions, multi-schema, CREATE FUNCTIONENUM → CHECK, views, role/IAM mapping, LANGUAGE sql functions
pg-migrations/multi-region.mdMulti-region, active-active, or HA questionsArchitecture, geographic partitioning
ORM Guides:
ReferenceWhen to LoadContains
orm-guides/overview.mdMigrating an ORM or using ORM locking with DSQLAdapter names, locking, and key gotchas for Django/EF Core/Hibernate/Rails/SQLAlchemy
Data Loading:
ReferenceWhen to LoadContains
data-loading.mdPlanning or running bulk loads with aurora-dsql-loaderFresh-vs-warm partitions, resume/retry, --on-conflict semantics, throughput diagnostics
System Diagnostics:
ReferenceWhen to LoadContains
system-diagnostics/workflow.mdMUST load at Workflow 12 entry — cluster performance diagnosticsPrerequisites, 5 diagnostic phases, temporal comparison, handoff
system-diagnostics/wait-events.mdALWAYS load when interpreting AAS resultsCanonical DSQL wait event descriptions and investigation guidance
system-diagnostics/promql-patterns.mdLoad when constructing PromQL queriesReusable query templates for AAS breakdown, top-SQL, temporal compare
Query Plan Explainability:
ReferenceWhen to LoadContains
query-plan/workflow.mdMUST load at Workflow 9 entry — gates all other filesTrigger criteria, context disambiguation, routing, phased workflow
query-plan/plan-interpretation.mdMUST load at Workflow 9 Phase 0DSQL node types, Node Duration math, estimation-error bands
query-plan/catalog-queries.mdMUST load at Workflow 9 Phase 0pg_class/pg_stats/pg_indexes SQL, correlated-predicate verification
query-plan/guc-experiments.mdMUST load at Workflow 9 Phase 0GUC experiment procedures, 30-second skip protocol
query-plan/report-format.mdMUST load at Workflow 9 Phase 0Required report structure, element checklist, support request template
query-plan/query-rewrites-generic.mdSHOULD load at Phase 0; sub-files on-demandIndex of 10 generic rewrite patterns
query-plan/query-rewrites-dsql-specific.mdSHOULD load at Phase 0; sub-files on-demandIndex 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-dsql MCP 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 + psql path instead: scripts/psql-connect.sh <cluster-id> --region <region> --command "SELECT ..." (mints an IAM token and runs via psql).

  • 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:

  1. readonly_query - Execute SELECT queries (returns list of dicts)

  2. transact - Execute DDL/DML statements in transaction (takes list of SQL statements)

  3. get_schema - Get table structure for a specific table

SQL Validation:

  1. dsql_lint - Validate SQL for DSQL compatibility and optionally auto-fix issues. Use before executing externally-sourced SQL.

Documentation & Knowledge:

  1. dsql_search_documentation - Search Aurora DSQL documentation

  2. dsql_read_documentation - Read specific documentation pages

  3. 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:

LimitDefaultVerify query
Max row modifications per transaction3,000aurora dsql transaction limits
Max data size per transaction10 MiBaurora dsql transaction limits
Max transaction duration5 minutesaurora dsql transaction limits
Max connections per cluster10,000aurora dsql connection limits
Auth token expiry15 minutesaurora dsql authentication token
Max connection duration60 minutesaurora dsql connection limits
Max indexes per table24 incl. PKaurora dsql index limits
Max columns per index8aurora dsql index limits
IDENTITY/SEQUENCE CACHE values1 or >= 65536aurora dsql sequence cache
Supported column data typesSee docsaurora 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

  1. Pick a connection path: confirm the aurora-dsql MCP targets your cluster; if not, use the CLI/psql path instead — see Choosing How to Connect. The steps below name MCP tools; the equivalent SQL runs the same way through psql-connect.sh --command "...".

  2. Explore: Use readonly_query with information_schema to list tables. Use get_schema for table structure.

  3. Query: Use readonly_query for SELECT queries. MUST include tenant_id in WHERE for multi-tenant apps. MUST build SQL with safe_query.build().

  4. Schema changes: Use transact with one DDL per transaction. MUST batch DML under 3,000 rows. MUST use CREATE INDEX ASYNC in a separate call. Use dsql_lint to validate first.

  5. Bulk load data: Use aurora-dsql-loader for CSV/TSV/Parquet. Load data-loading.md for details. Use --dry-run first.


Performance Routing

When the user reports a performance problem, use this table to select the correct workflow:

User signalRoute to
General performance complaint, "cluster is slow", "something changed", latency regression, no specific query identifiedWorkflow 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 stormsWorkflow 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
  1. Create tenant-owned tables with tenant_id using separate transact calls

  2. Use composite tenant FKs for tenant-owned parents and ordinary FKs for shared parents

  3. Create tenant and query-pattern indexes with separate CREATE INDEX ASYNC calls

  4. Verify 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 use TEXT when the column is opaque to the database; ASK the user. For JSONB arrays, expand at query time with jsonb_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.

  1. Validate DDL with dsql_lint(sql=..., fix=true) — handle diagnostics per dsql-lint.md

  2. Execute the reviewed fixed_sql when present, otherwise the reviewed source statement

  3. Add column in its own transact call

  4. Populate existing rows with UPDATE (batched under 3,000 rows)

  5. Verify with readonly_query COUNT

  6. Create an index if needed: validate then execute the reviewed DDL in its own transact call

  • MUST issue each ALTER TABLE in its own transact call — DSQL rejects multi-DDL transactions with multiple ddl statements not supported in a transaction

  • MUST 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.

  1. Validate with --dry-run first

  2. Run with --manifest-dir on persistent storage (not /tmp — tmpfs on AL2023, lost on crash) and --header if file has a header row

  3. On failure: resume with --resume-job-id; for duplicates use --on-conflict do-nothing

  4. For 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
  1. MUST authorize the caller against the tenant — format validation does not establish authorization

  2. MUST build SQL with safe_query.build() — use allow()/regex() for values (emits 'v'), ident() for table/column names (emits "v"). See input-validation.md

  3. MUST include tenant_id in 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

  • awsknowledge returns no results: Use the default limits in the table above and note that limits should be verified against DSQL documentation.

  • dsql_lint unavailable 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 the 40001 retry 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

references/limits-and-error-codes.md

Limits and Error Codes

Every DSQL limit, rejection and cluster quota with its SQLSTATE and exact message. Load it before sizing batches, keys or index sets, and to identify a 54000, 0A000 or 54011 error. Other errors are in troubleshooting.md.

Match on the message rather than the code. 54000 and 0A000 each cover more than a dozen of the rows below, so the code alone does not identify which row you are on. This is a lookup rule for these tables, not a retry rule — classification elsewhere in the skill is SQLSTATE-based, and 40001 remains the only retryable code (see occ-retry-patterns.md).

MUST match a stable prefix, not the whole string, and match it case-insensitively — case varies even within one family (Datatype limit … for char/varchar, datatype limit … for text). <n>, <type> and ... in the Message column are values DSQL interpolates at run time, so an equality test against the cell never matches. If no message matches, SHOULD fall back to the SQLSTATE class and verify the current limit via awsknowledge — message text is not a stable contract.

Values marked observed were measured on a single-Region cluster (PostgreSQL 16 compatibility) rather than taken from the documentation. Where an observed value contradicts the quotas documentation, the row says so. SHOULD size against the observed value, which is what DSQL enforced when measured, and tell the user the documented value differs. To re-check one before a design decision depends on it, test it on a cluster; the quotas page is what it already contradicts.

Run dsql_lint to catch unsupported features before execution; use this section for the limits, which are only observable at run time.

Exceeded Limits

LimitValueSQLSTATEMessage
Row modifications per transaction3,00054000transaction row limit exceeded
Transaction size10 MiB, incl. per-row and per-index overhead (see below)54000transaction size limit 10mb exceeded, with DETAIL: Current transaction size <n>mb > 10mb
Transaction age5 minutes54000transaction age limit of 300s exceeded, with DETAIL: Current transaction age <n>s exceeds 300s
Query temp space128 MiB; docs give 53200 and other text54000query requires more than allowed temp space of 131072 KB to execute
Extended statistics per table554000more than 5 extended statistics per table are not allowed
Schemas per database10, excluding public and sys54000more than 10 schemas not allowed
Indexes per table24, counting every index — see below54000more than 24 indexes per table are not allowed
Primary key or index key size~1,981 bytes observed; docs say 1 KiB54000key size too large
Declared key size2,000 bytes, rejected at DDL time54000key size greater than 2000 bytes not supported
Row size2 MiB54000maximum row size exceeded
Non-index column size1 MiB; docs give the message below, a per-datatype one was seen54000docs: maximum column size exceeded; observed: datatype limit greater than 1048576 bytes not supported for <type>
View definition size131–524 KiB of SQL text observed, varies by shape; docs say 2 MiB54000view definition too large
char declared size4,096 bytes, rejected at DDL time54000Datatype limit greater than 4096 bytes not supported for char
varchar declared size65,535 bytes, rejected at DDL time54000Datatype limit greater than 65535 bytes not supported for varchar
text value1 MiB stored, rejected at write time54000datatype limit greater than 1048576 bytes not supported for text
bytea value1 MiB stored, rejected at write time54000datatype limit greater than 1048576 bytes not supported for bytea
json / jsonb value1 MiB stored, rejected at write time54000datatype limit greater than 1048576 bytes not supported for jsonb
Columns per index or primary key854011more than 8 column keys in an index are not supported
Columns per table, no primary key256 accepted, 257 rejected; docs and message both say 25554011tables can have at most 255 columns
Columns per table, with primary key256 accepted, 257 rejected; message names an index54011cannot use more than 256 columns in an index
Extended-statistics target10022023statistics target <n> exceeds maximum allowed value of 100
numeric precision1,00022023NUMERIC precision <n> must be between 1 and 1000

Several of these behave in ways the limit alone does not convey:

  • The per-value 1 MiB limit is a hard bound on high-entropy data. For random text, base64, bytea and jsonb, 1,048,576 bytes is the largest value accepted and 1,048,577 the first rejected — nothing fails early. Compressible values go much further. Size against raw byte count; compression only ever buys headroom.

  • The 10 MiB transaction limit also counts index writes. The check runs at COMMIT against an accounted size that adds a cost per row and per secondary index entry written. The per-entry cost grows with the index key plus the primary key: small for int, uuid or timestamptz keys, several times the key width for wide text keys. A 500-row batch committed at most 9.93 MiB of raw data with no secondary index, and 9.11 MiB with four on 100-byte text keys. The row limit is documented as independent of secondary indexes; the size limit is not, and its accounting is undocumented. Large compressible values, such as JSON over a few KB, can count below their raw size. To size a batch, read the error: DETAIL: Current transaction size <n>mb > 10mb is the exact accounted size, so one over-limit trial on the real schema gives the ratio to scale by.

  • The key-size budget is shared, in bytes, by every key column. One column holds ~1,981 bytes and each additional key column costs ~7 more, so an 8-column key gets ~241 bytes each. Bytes, not characters — a 4-byte UTF-8 character key holds ~495 characters. A secondary index key also carries the table's primary key columns, so a 500-byte primary key leaves ~1,474 bytes for the index columns. Separately, DDL rejects a key whose declared sizes sum past 2,000 bytes, leaving the primary key out of that sum for a secondary index; a varchar(2000) key therefore passes CREATE and still fails on write above ~1,981 bytes. The quotas page lists the primary key and secondary index as two separate 1 KiB budgets, but DSQL enforces the single shared budget above: give the user these figures, and note that the documentation says 1 KiB.

  • The view-definition limit is a 512 KiB internal budget, not a text length. How much SQL fits depends on the query's structure, so treat ~120 KiB of definition text as a working ceiling and size by trial when a view approaches it.

  • Every index counts toward the 24: the primary key, the index behind each UNIQUE constraint, and every CREATE [UNIQUE] INDEX ASYNC, including one still building (indisvalid = f). A table with a primary key and one UNIQUE constraint has 22 slots left; a table with no primary key has no hidden index and holds 24. Count with SELECT count(*) FROM pg_index WHERE indrelid = 'tbl'::regclass. DROP INDEX frees a slot.

  • char and varchar limits are enforced on the declared size at DDL time, so an oversized declaration fails at CREATE TABLE, not on first write.

  • Dropped columns keep counting. The documented ceiling is 1,600 cumulative columns including dropped ones, so a table churned by repeated ADD COLUMN/DROP COLUMN during a migration can hit 54011 while holding far fewer live columns. Recreate the table rather than continuing to churn it, with user approval, following ddl-migrations/overview.md.

Rejections and Constraint Violations

Unsupported-feature list: PostgreSQL compatibility — unsupported features. Index syntax: CREATE INDEX syntax support.

These are not limits — the feature or the value is refused outright.

CauseSQLSTATEMessage
Non-immutable function in an index expression42P17functions in index expression must be marked IMMUTABLE
Non-immutable generated-column expression42P17generation expression is not immutable
serial column type42704type "serial" does not exist
Array column type0A000datatype text[] not supported — the declared type is echoed back
Sort direction on an index key0A000specifying sort order not supported for index keys
Operator class on an index key0A000opclass not supported for index keys
Index on an unsupported column type0A000datatype <type> is not supported in a key
CREATE INDEX without ASYNC0A000unsupported mode. please use CREATE INDEX ASYNC.
CREATE INDEX CONCURRENTLY0A000CONCURRENTLY not supported for CREATE INDEX
ALTER TABLE ADD COLUMN with any inline constraint0A000ALTER TABLE ADD COLUMN with constraint not supported
ALTER COLUMN ... SET DATA TYPE0A000unsupported ALTER TABLE ALTER COLUMN ... SET DATA TYPE statement
ALTER COLUMN ... SET STATISTICS, at any value0A000unsupported ALTER TABLE ALTER COLUMN ... SET STATISTICS statement
CREATE PROCEDURE0A000PROCEDURE is not supported
CREATE DATABASE0A000unsupported statement: Createdb
Post-creation foreign key without NOT VALID0A000unsupported ALTER TABLE ADD CONSTRAINT statement
Synchronous VALIDATE CONSTRAINT0A000unsupported ALTER TABLE VALIDATE CONSTRAINT statement
Foreign key violation — not retryable23503insert or update on table ... violates foreign key constraint ...
Duplicate against a unique index still building23505duplicate key value violates unique constraint ...
Any statement issued after a failure inside BEGIN25P02current transaction is aborted, commands ignored until end of transaction block
Protocol message over 10 MiBnoneNo error reaches the client — see below

These mislead in practice:

  • 25P02 masks the real error. It is the code an agent sees most often, because anything that keeps issuing statements after a failure inside a transaction block gets it in place of the original cause. Read the first error in the transaction, not the last.

  • An oversized protocol message closes the connection with no error message. The client sees only SSL SYSCALL error: EOF detected, which is indistinguishable from a transient network fault, so a naive retry resends the same oversized statement forever. Treat an EOF on the first statement after a large one as a size problem, not a network one. Note the AWS documentation lists 08P01 / FATAL: invalid message length for this case; that error is not delivered. If you do see 08P01: invalid message length, that is this case and the behaviour has changed — trust the error.

Any EOF on a statement that could have committed — COMMIT, or any write in autocommit mode — leaves the commit outcome unknown, whatever the cause, because the connection closed before the server replied. This applies to the oversized-message case above and equally to an EOF the agent classifies as a network fault — the size discriminator tells you why the connection dropped, not whether the write landed. Before resending, an agent MUST reconnect and confirm whether the write committed. Designing the write to be idempotent removes the need for that check, but only if it was already idempotent — it is not something that can be applied after the EOF arrives, and a bare retry of a non-idempotent write such as UPDATE accounts SET balance = balance - 100 double-applies it. See occ-retry-patterns.md.

If the outcome cannot be confirmed, an agent MUST NOT retry. A blind balance = balance - 100 has no observable trace that distinguishes "applied once" from "not applied", so there is nothing to query. MUST report the unresolved write to the user with the transaction's identifying values and stop; a duplicated debit is worse than a reported gap. Avoid the situation rather than resolve it: write a correlation id the transaction itself records, so the question becomes answerable next time.

The threshold is the protocol message size, which a client does not see directly: a batched or parameterised multi-row insert can exceed it well below 10 MiB of visible data. If you cannot measure it, reduce the batch size until the EOF stops — after confirming, as above, that the previous attempt did not commit.

Cluster Quotas

From the Aurora DSQL quotas documentation. Unlike the tables above, these are not verified here — they need provisioned resources to exercise, so treat the values as documented rather than observed.

QuotaValueSQLSTATEMessage when exceeded
Tables per database1,00054000creating more than 1000 tables not allowed
Views per database5,00054000creating more than 5000 views not allowed
Sequences per database5,00054000creating more than 5000 sequences is not allowed
Single-Region clusters per account, per Region20 (increasable)APIYou have reached the cluster limit.
Multi-Region clusters per account, per Region5 (increasable)APIYou have reached the cluster limit.
Storage per cluster10 TiB, increasable to 256 TiB53100Current cluster size exceeds cluster size limit.
Connections per cluster10,00053300Unable to accept connection, too many open connections.
New connections per second100 sustained, 1,000 burst53400Unable to accept connection, rate exceeded.
Concurrent restore jobs4—No error code documented
CDC streams per cluster5APIYou have reached the stream limit.

The cluster-count and CDC rows surface as the control-plane API error ServiceQuotaExceededException: 402, not a SQLSTATE, so they never reach a SQL client.

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

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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)
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