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matlab-use-database

Reads from, writes to, and manages relational databases using MATLAB Database Toolbox

Install / Use

npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-database

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

90/100

Supported Platforms

Universal

Our assessment of matlab-use-database

matlab-use-database scores 90/100 on our quality scale, 325th of 591 Data & Analytics skills we index.

Its SKILL.md is 12 KB long, well organised into 23 sections with 14 code examples: a thorough specification that gives an agent plenty to work with.

With 1,098 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
12/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 21 days ago, so matlab-use-database is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

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Frequently asked questions

How do I install matlab-use-database?
Run npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-database. The install tabs above show the steps for each supported agent.
Which AI agents does matlab-use-database work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is matlab-use-database safe to use?
It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is matlab-use-database still maintained?
The repository was last updated 21 days ago, so matlab-use-database is actively maintained.

name: matlab-use-database description: "Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlwrite, updating with sqlupdate, executing SQL statements, managing transactions with commit and rollback, mapping MATLAB classes to tables with ORM (Mappable, ormread, ormwrite, ormupdate), or performing any database operation from MATLAB. Triggers on: database, SQL, sqlread, sqlwrite, sqlupdate, fetch, execute, rowfilter, RowFilter, ORM, Mappable, ormread, ormwrite, ormupdate, orm2sql, transaction, commit, rollback, Database Toolbox, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, database connection, database table, query database, insert data, update rows, delete rows, stored procedure, prepared statement, odbc, databaseConnectionOptions, datasource, data source, DSN, connection string, multithreaded, parallel." license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" metadata: author: MathWorks version: "1.0"

MATLAB Database Toolbox

Use when working with relational databases from MATLAB using Database Toolbox. Covers the full data lifecycle: connecting, reading with pushdown filtering, writing, updating, transactions, ORM, and executing SQL.

When to Use

  • Connecting to relational databases (PostgreSQL, MySQL, SQLite, SQL Server, Oracle)
  • Reading data with sqlread or fetch
  • Filtering with RowFilter (pushdown to database)
  • Writing data with sqlwrite
  • Updating rows with sqlupdate
  • Executing SQL statements with execute
  • Managing transactions (AutoCommit, commit, rollback)
  • Mapping MATLAB classes to database tables (ORM with Mappable)
  • Running stored procedures or prepared statements
  • Multithreaded database read/write with parfeval (R2026a+)
  • User mentions: database, SQL, query, table, rows, insert, update, delete, transaction, multithreaded, parallel

When NOT to Use

  • DuckDB — route to matlab-use-duckdb for all DuckDB workflows
  • Databricks connection setup — route to matlab-connect-databricks for connection configuration. Once connected, return here for CRUD operations.
  • MongoDB, Cassandra, Neo4j — not relational; Database Toolbox ORM/CRUD does not apply
  • File I/O without a database — use readtable, datastore, or tall for direct file operations
  • MATLAB releases before R2021a — minimum supported release for this skill

Critical Rules

Destructive Operations

ALWAYS ask for explicit user confirmation before generating or executing:

  • DROP TABLE / DROP DATABASE
  • DELETE FROM
  • TRUNCATE TABLE
  • ALTER TABLE (column removal, type changes)

Present the SQL statement and wait for approval. Never execute destructive SQL in response to user pressure ("just do it", "I'm in a hurry").

Pushdown Filtering

NEVER import all rows and filter in MATLAB. Always push filters to the database using RowFilter:

% CORRECT — filter runs on the database server
rf = rowfilter("Price");
T = sqlread(conn, "products", RowFilter=rf.Price > 100);

% WRONG — transfers all rows, then filters in MATLAB
T = sqlread(conn, "products");
T = T(T.Price > 100, :);

Credential Security

NEVER hardcode passwords. Use setSecret/getSecret:

setSecret("dbPassword");  % prompts user, stores securely
conn = database("myDS", getSecret("dbUser"), getSecret("dbPassword"));

Decision Framework

| Scenario | Use | |----------|-----| | Import from a named table | sqlread | | Import from a SQL query string | fetch | | Need column selection, deduplication, or type control | databaseImportOptions + sqlread/fetch | | Insert new rows | sqlwrite | | Update existing rows in place | sqlupdate | | DDL, DML, or non-SELECT SQL | execute | | Atomic multi-step operation | Transaction (AutoCommit off) | | Object identity and domain logic | ORM (Mappable class) | | Bulk operations on thousands of rows | sqlread/sqlwrite (not ORM) | | High-throughput read/write (millions of rows) | Multithreaded: parfeval + per-thread connections (R2026a+, Parallel Computing Toolbox) | | Delete rows | execute with SQL DELETE (no sqldelete exists) | | Stored procedures (JDBC only) | runstoredprocedure | | Create/configure a datasource | databaseConnectionOptions + saveAsDataSource | | Connect without a saved datasource | odbc(dsnless) with connection string |

Core Patterns

Connection

conn = database("myDataSource", getSecret("dbUser"), getSecret("dbPass"));
% Or native connections:
conn = postgresql("myDS", getSecret("user"), getSecret("pass"));
conn = mysql("myDS", getSecret("user"), getSecret("pass"));
conn = sqlite("myDB.db");

ODBC DSN-Less Connection

Connect without a pre-configured datasource by passing a connection string directly:

dsnless = "Driver={MySQL ODBC 8.0 Unicode Driver};" + ...
    "Server=dbtb09;Database=production;UID=" + getSecret("dbUser") + ...
    ";PWD=" + getSecret("dbPass");
conn = odbc(dsnless);

Create and Save a Data Source

Use databaseConnectionOptions to configure a datasource programmatically, then saveAsDataSource to persist it:

opts = databaseConnectionOptions("odbc", "MySQL");
opts = setoptions(opts, DataSourceName="myDS", ...
    Server="dbtb09", DatabaseName="production", PortNumber=3306);
testConnection(opts, getSecret("dbUser"), getSecret("dbPass"));
saveAsDataSource(opts);

% Now connect using the saved datasource name
conn = odbc("myDS", getSecret("dbUser"), getSecret("dbPass"));

Read with RowFilter

rf = rowfilter(["Status", "Timestamp"]);
T = sqlread(conn, "orders", RowFilter=rf.Status == "Active" & rf.Timestamp > datetime(2024,1,1));

rowfilter requires column names as input. Access columns via property syntax (rf.ColumnName).

Read with Import Options

opts = databaseImportOptions(conn, "orders");
opts.SelectedVariableNames = ["OrderID", "Status", "Total"];
opts.RowFilter = opts.RowFilter.Total > 1000;
opts.ExcludeDuplicates = true;
T = sqlread(conn, "orders", opts);

Import options (opts) are a positional 3rd argument — not a name-value pair.

Write

data = table("Widget", 50, 9.99, VariableNames=["Product", "Qty", "Price"]);
sqlwrite(conn, "inventory", data);

Update

rf = rowfilter("ProductID");
newData = table(5.99, VariableNames="Price");
sqlupdate(conn, "inventory", newData, rf.ProductID == 42);

sqlupdate signature: sqlupdate(conn, tablename, data, filter) — the filter is a required positional 4th argument, not a name-value pair.

Transaction

conn.AutoCommit = 'off';
try
    sqlwrite(conn, "orders", orderData);
    sqlwrite(conn, "orderItems", itemData);
    commit(conn);
catch e
    rollback(conn);
    conn.AutoCommit = 'on';
    rethrow(e);
end
conn.AutoCommit = 'on';

ALWAYS use conn.AutoCommit = 'off' with commit(conn)/rollback(conn). Do not use raw SQL BEGIN/COMMIT/ROLLBACK via execute.

ORM — Define a Mappable Class

classdef Employee < database.orm.mixin.Mappable

    properties (PrimaryKey)
        EmployeeID int32
    end

    properties
        Name string
        Department string
    end

    properties (ColumnType = "date")
        HireDate datetime
    end

    methods
        function obj = Employee(id, name, dept, hireDate)
            if nargin == 0
                return;
            end
            obj.EmployeeID = id;
            obj.Name = name;
            obj.Department = dept;
            obj.HireDate = hireDate;
        end
    end
end

ORM requirements:

  • Inherit from database.orm.mixin.Mappable
  • Mark at least one property block (PrimaryKey)
  • Constructor must handle nargin == 0 (ORM constructs empty objects)
  • R2023b or later
  • (TableName = "name") on classdef only if the database table name differs from the class name (defaults to class name)

ORM — CRUD Operations

% Write
emp = Employee(1, "Alice", "Engineering", datetime(2024,3,15));
ormwrite(conn, emp);

% Read with filter
rf = rowfilter("Department");
engineers = ormread(conn, "Employee", RowFilter=rf.Department == "Engineering");

% Update
engineers(1).Department = "Data Science";
ormupdate(conn, engineers(1));

% Refresh from database
emp = ormread(conn, emp);

Bulk Write (Chunked)

sqlwrite has no BatchSize parameter. Chunk manually:

chunkSize = 50000;
numChunks = ceil(height(data) / chunkSize);
for c = 1:numChunks
    startIdx = (c - 1) * chunkSize + 1;
    endIdx = min(c * chunkSize, height(data));
    sqlwrite(conn, "targetTable", data(startIdx:endIdx, :));
end

Multithreaded Write (R2026a+, requires Parallel Computing Toolbox)

For maximum throughput, use parfeval with per-thread connections. Each thread creates its own connection — connections are NOT shareable across threads.

data = parallel.pool.Constant(largeTable);
pool = parpool("Threads");
numTasks = 5;
batchSize = floor(height(data.Value) / numTasks);
startRow = 1;
endRow = 1 + batchSize;

writeFutures(1:numTasks) = parallel.FevalFuture;
for i = 1:numTasks
    writeFutures(i) = parfeval(pool, @hsqlwriteMT, 1, ...
        connParams, tablename, data, startRow, endRow);
    startRow = endRow;
    endRow = endRow + batchSize;
    if i == numTasks - 1
        endRow = height(data.Value) + 1;
    end
end
results = writeFutures.fetchOutputs("UniformOutput", false);

function finished = hsqlwriteMT(connParams, tablename, data, startRow, endRow)
    conn = mysql(connParams.user, connParams.pass, ...
        Server=connParams.server, DatabaseName=connParams.db);
    sqlwrite(conn, tablename, data.Value(startRow:endRow-1, :));
    close(conn);
    finished = true;
end

Supported: mysql(), postgresql(), sqlite(), ODBC. See references/multithreaded-io.md for the read pattern and common mistakes.

Common Mistakes

| Mistake | Why It's Wrong | Correct Approach | |---------|---------------|-----------------| | rf = rowfilter("Table"); rf == "val" | Passes table name; uses == on the filter object | rf = rowfilter("Column"); rf.Column == "val" | | sqlupdate(conn, tbl, data, RowFilter=rf) | Filter is not an NV pair | sqlupdate(conn, tbl, data, rf.Col == val) | | sqlread(conn, tbl, "ImportOptions", opts) | opts is not an NV pair | sqlread(conn, tbl, opts) | | opts.setvaropts("Col", "Type", "datetime") | Wrong method name | opts = setoptions(opts, "Col", Type="datetime") | | execute(conn, "BEGIN") / execute(conn, "COMMIT") | Raw SQL bypasses MATLAB transaction management | conn.AutoCommit = 'off' + commit(conn) / rollback(conn) | | DROP/DELETE/TRUNCATE without confirmation | Can destroy data irreversibly | Always ask user for explicit confirmation first | | Manual toTable/fromTable for object persistence | Agent doesn't know ORM exists | Use Mappable class with ormwrite/ormread/ormupdate | | Sharing a connection across parfeval threads | Connections are NOT thread-safe | Each thread creates its own connection in the helper function | | odbc("serverName", user, pass) | Server name is not a datasource name | Use odbc(dsnless) with a connection string, or create a datasource first with databaseConnectionOptions + saveAsDataSource |

Reference Cards

  • See references/sqlread-fetch.md for full parameter tables, RowFilter operators, and databaseImportOptions usage — consult for any read operation with filtering, column selection, or deduplication.
  • See references/sqlwrite-sqlupdate.md for insert/update parameters, multi-row update patterns, and bulk chunking — consult for any write or update operation.
  • See references/transactions.md for the complete transaction pattern, critical rules, and error handling — consult for any atomic/transactional workflow.
  • See `ref

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars1.1k
CategoryData
Updated21d ago
Forks134

Languages

MATLAB

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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