questdb · javier · Dec 10, 2025 · Dec 10, 2025 · Dec 10, 2025 · Dec 10, 2025
diff --git a/documentation/cookbook/demo-data-schema.md b/documentation/cookbook/demo-data-schema.md
@@ -1,5 +1,5 @@
 ---
-title: Demo Data Schema
+title: Demo data schema
 sidebar_label: Demo data schema
 description: Schema and structure of the FX market data and cryptocurrency trades available on demo.questdb.io
 ---
@@ -19,11 +19,11 @@ The demo instance provides two independent datasets:
 
 ---
 
-## FX Market Data (Simulated)
+## FX market data (simulated)
 
 The FX dataset contains simulated foreign exchange market data for 30 currency pairs. We fetch real reference prices from Yahoo Finance every few seconds, but all order book levels and price updates are generated algorithmically based on these reference prices.
 
-### core_price Table
+### core_price table
 
 The `core_price` table contains individual FX price updates from various liquidity providers. Each row represents a bid/ask quote update for a specific currency pair from a specific ECN.
 
@@ -32,16 +32,16 @@ The `core_price` table contains individual FX price updates from various liquidi
 ```sql title="core_price table structure"
 CREATE TABLE 'core_price' (
     timestamp TIMESTAMP,
-    symbol SYMBOL CAPACITY 16384 CACHE,
-    ecn SYMBOL CAPACITY 256 CACHE,
+    symbol SYMBOL,
+    ecn SYMBOL,
     bid_price DOUBLE,
     bid_volume LONG,
     ask_price DOUBLE,
     ask_volume LONG,
-    reason SYMBOL CAPACITY 256 CACHE,
+    reason SYMBOL,
     indicator1 DOUBLE,
     indicator2 DOUBLE
-) timestamp(timestamp) PARTITION BY HOUR TTL 3 DAYS WAL;
+) timestamp(timestamp) PARTITION BY HOUR TTL 3 DAYS;
 ```
 
 #### Columns
@@ -58,7 +58,7 @@ CREATE TABLE 'core_price' (
 
 The table tracks **30 currency pairs**: EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD, EURJPY, GBPJPY, EURGBP, AUDJPY, CADJPY, NZDJPY, EURAUD, EURNZD, AUDNZD, GBPAUD, GBPNZD, AUDCAD, NZDCAD, EURCAD, EURCHF, GBPCHF, USDNOK, USDSEK, USDZAR, USDMXN, USDSGD, USDHKD, USDTRY.
 
-#### Sample Data
+#### Sample data
 
 ```questdb-sql demo title="Recent core_price updates"
 SELECT * FROM core_price
@@ -81,7 +81,7 @@ LIMIT -10;
 | 2025-12-18T11:46:13.066700Z | CADJPY | Currenex | 113.63    | 20300827   | 114.11    | 19720915   | normal          | 0.55       |            |
 | 2025-12-18T11:46:13.071607Z | NZDJPY | Currenex | 89.95     | 35284228   | 90.46     | 30552528   | liquidity_event | 0.69       |            |
 
-### market_data Table
+### market_data table
 
 The `market_data` table contains order book snapshots for currency pairs. Each row represents a complete view of the order book at a specific timestamp, with bid and ask prices and volumes stored as 2D arrays.
 
@@ -109,7 +109,7 @@ The arrays are structured so that:
 - `asks[1]` contains ask prices (ascending order - lowest first)
 - `asks[2]` contains corresponding ask volumes
 
-#### Sample Query
+#### Sample query
 
 ```questdb-sql demo title="Recent order book snapshots"
 SELECT timestamp, symbol,
@@ -132,7 +132,7 @@ LIMIT -5;
 
 Each order book snapshot contains 40 bid levels and 40 ask levels.
 
-### fx_trades Table
+### fx_trades table
 
 The `fx_trades` table contains simulated FX trade executions. Each row represents a trade that executed against the order book, with realistic partial fills and level walking.
 
@@ -150,7 +150,7 @@ CREATE TABLE 'fx_trades' (
     quantity DOUBLE,
     counterparty SYMBOL,
     order_id UUID
-) timestamp(timestamp) PARTITION BY HOUR TTL 1 MONTH WAL;
+) timestamp(timestamp) PARTITION BY HOUR TTL 1 MONTH;
 ```
 
 #### Columns
@@ -166,7 +166,7 @@ CREATE TABLE 'fx_trades' (
 - **`counterparty`** - 20-character LEI (Legal Entity Identifier) of the counterparty
 - **`order_id`** - Parent order identifier (multiple trades can share the same `order_id` for partial fills)
 
-#### Sample Data
+#### Sample data
 
 ```questdb-sql demo title="Recent FX trades"
 SELECT * FROM fx_trades
@@ -189,48 +189,48 @@ LIMIT -10;
 | 2026-01-12T12:18:57.509773474Z | GBPUSD | Currenex | ae6b771b-5abd-44c7-9e0e-3527ce6fb5b4 | sell | false   | 1.3404  | 62305.0  | 006728CF215E44412D18 | 54ff8191-1891-4a5c-8b67-d5cd961ec5e8 |
 | 2026-01-12T12:18:57.334732460Z | USDTRY | EBS      | 469637a5-6553-4aad-aad9-f7114c8a442d | sell | true    | 43.1    | 101177.0 | 002CAC92E93AB4B3D30C | 2ce77a03-0f21-4241-8ca7-903080848dc0 |
 
-### FX Materialized Views
+### FX materialized views
 
 The FX dataset includes several materialized views providing pre-aggregated data at different time intervals:
 
-#### Best Bid/Offer (BBO) Views
+#### Best bid/offer (BBO) views
 
 - **`bbo_1s`** - Best bid and offer aggregated every 1 second
 - **`bbo_1m`** - Best bid and offer aggregated every 1 minute
 - **`bbo_1h`** - Best bid and offer aggregated every 1 hour
 - **`bbo_1d`** - Best bid and offer aggregated every 1 day
 
-#### Core Price Aggregations
+#### Core price aggregations
 
 - **`core_price_1s`** - Core prices aggregated every 1 second
 - **`core_price_1d`** - Core prices aggregated every 1 day
 
-#### Market Data OHLC
+#### Market data OHLC
 
 - **`market_data_ohlc_1m`** - Open, High, Low, Close candlesticks at 1-minute intervals
 - **`market_data_ohlc_15m`** - OHLC candlesticks at 15-minute intervals
 - **`market_data_ohlc_1d`** - OHLC candlesticks at 1-day intervals
 
-#### FX Trades OHLC
+#### FX trades OHLC
 
 - **`fx_trades_ohlc_1m`** - OHLC candlesticks from trade executions at 1-minute intervals
 - **`fx_trades_ohlc_1h`** - OHLC candlesticks from trade executions at 1-hour intervals
 
 These views are continuously updated and optimized for dashboard and analytics queries on FX data.
 
-### FX Data Volume
+### FX data volume
 
 - **`market_data`**: Approximately **160 million rows** per day (order book snapshots)
 - **`core_price`**: Approximately **73 million rows** per day (price updates across all ECNs and symbols)
 - **`fx_trades`**: Approximately **5.1 million rows** per day (trade executions)
 
 ---
 
-## Cryptocurrency Trades (Real)
+## Cryptocurrency trades (real)
 
 The cryptocurrency dataset contains **real market data** streamed live from the OKX exchange using FeedHandler. These are actual executed trades, not simulated data.
 
-### trades Table
+### trades table
 
 The `trades` table contains real cryptocurrency trade data. Each row represents an actual executed trade for a cryptocurrency pair.
 
@@ -243,7 +243,7 @@ CREATE TABLE 'trades' (
     price DOUBLE,
     amount DOUBLE,
     timestamp TIMESTAMP
-) timestamp(timestamp) PARTITION BY DAY WAL;
+) timestamp(timestamp) PARTITION BY DAY;
 ```
 
 #### Columns
@@ -254,9 +254,9 @@ CREATE TABLE 'trades' (
 - **`price`** - Execution price of the trade
 - **`amount`** - Trade size (volume in base currency)
 
-The table tracks **12 cryptocurrency pairs**: ADA-USDT, AVAX-USD, BTC-USDT, DAI-USD, DOT-USD, ETH-BTC, ETH-USDT, LTC-USD, SOL-BTC, SOL-USD, UNI-USD, XLM-USD.
+The table tracks **12 cryptocurrency pairs**: ADA-USDT, AVAX-USDT, BTC-USDT, DAI-USDT, DOT-USDT, ETH-BTC, ETH-USDT, LTC-USDT, SOL-BTC, SOL-USDT, UNI-USDT, XLM-USDT.
 
-#### Sample Data
+#### Sample data
 
 ```questdb-sql demo title="Recent cryptocurrency trades"
 SELECT * FROM trades
@@ -268,40 +268,40 @@ LIMIT -10;
 | symbol   | side | price   | amount     | timestamp                   |
 | -------- | ---- | ------- | ---------- | --------------------------- |
 | BTC-USDT | buy  | 85721.6 | 0.00045714 | 2025-12-18T19:31:11.203000Z |
-| BTC-USD  | buy  | 85721.6 | 0.00045714 | 2025-12-18T19:31:11.203000Z |
+| BTC-USDT | buy  | 85721.6 | 0.00045714 | 2025-12-18T19:31:11.203000Z |
 | BTC-USDT | buy  | 85726.6 | 0.00001501 | 2025-12-18T19:31:11.206000Z |
-| BTC-USD  | buy  | 85726.6 | 0.00001501 | 2025-12-18T19:31:11.206000Z |
+| BTC-USDT | buy  | 85726.6 | 0.00001501 | 2025-12-18T19:31:11.206000Z |
+| BTC-USDT | buy  | 85726.9 | 0.000887   | 2025-12-18T19:31:11.206000Z |
 | BTC-USDT | buy  | 85726.9 | 0.000887   | 2025-12-18T19:31:11.206000Z |
-| BTC-USD  | buy  | 85726.9 | 0.000887   | 2025-12-18T19:31:11.206000Z |
 | BTC-USDT | buy  | 85731.3 | 0.00004393 | 2025-12-18T19:31:11.206000Z |
-| BTC-USD  | buy  | 85731.3 | 0.00004393 | 2025-12-18T19:31:11.206000Z |
+| BTC-USDT | buy  | 85731.3 | 0.00004393 | 2025-12-18T19:31:11.206000Z |
+| ETH-USDT | sell | 2827.54 | 0.006929   | 2025-12-18T19:31:11.595000Z |
 | ETH-USDT | sell | 2827.54 | 0.006929   | 2025-12-18T19:31:11.595000Z |
-| ETH-USD  | sell | 2827.54 | 0.006929   | 2025-12-18T19:31:11.595000Z |
 
-### Cryptocurrency Materialized Views
+### Cryptocurrency materialized views
 
 The cryptocurrency dataset includes materialized views for aggregated trade data:
 
-#### Trades Aggregations
+#### Trades aggregations
 
 - **`trades_latest_1d`** - Latest trade data aggregated daily
 - **`trades_OHLC_15m`** - OHLC candlesticks for cryptocurrency trades at 15-minute intervals
 
 These views are continuously updated and provide faster query performance for cryptocurrency trade analysis.
 
-### Cryptocurrency Data Volume
+### Cryptocurrency data volume
 
 - **`trades`**: Approximately **3.7 million rows** per day (real cryptocurrency trades)
 
 ---
 
-## Data Retention
+## Data retention
 
 **FX tables** (`core_price` and `market_data`) use a **3-day TTL (Time To Live)**, meaning data older than 3 days is automatically removed. This keeps the demo instance responsive while providing sufficient recent data.
 
 **Cryptocurrency trades table** has **no retention policy** and contains historical data dating back to **March 8, 2022**. This provides over 3 years of real cryptocurrency trade history for long-term analysis and backtesting.
 
-## Using the Demo Data
+## Using the demo data
 
 You can run queries against both datasets directly on [demo.questdb.com](https://demo.questdb.io). Throughout the Cookbook, recipes using demo data will include a direct link to execute the query.
 

diff --git a/documentation/cookbook/index.md b/documentation/cookbook/index.md
@@ -1,12 +1,12 @@
 ---
-title: Cookbook Overview
+title: Cookbook overview
 sidebar_label: Overview
 description: Quick recipes and practical examples for common QuestDB tasks and queries
 ---
 
 The Cookbook is a collection of **short, actionable recipes** that demonstrate how to accomplish specific tasks with QuestDB. Each recipe follows a problem-solution-result format, making it easy to find and apply solutions quickly.
 
-## What is the Cookbook?
+## What is the cookbook?
 
 Unlike comprehensive reference documentation, the Cookbook focuses on practical examples for:
 
@@ -24,15 +24,15 @@ The Cookbook is organized into three main sections:
 - **Programmatic** - Language-specific client examples and integration patterns
 - **Operations** - Deployment, configuration, and operational tasks
 
-## Running the Examples
+## Running the examples
 
 **Most recipes run directly on our [live demo instance at demo.questdb.com](https://demo.questdb.com)** without any local setup. Queries that can be executed on the demo site are marked with a direct link to run them.
 
 For recipes that require write operations or specific configuration, the recipe will indicate what setup is needed.
 
 The demo instance contains live FX market data with tables for core prices and order book snapshots. See the [Demo Data Schema](/docs/cookbook/demo-data-schema/) page for details about available tables and their structure.
 
-## Using the Cookbook
+## Using the cookbook
 
 Each recipe follows a consistent format:
 

diff --git a/documentation/cookbook/integrations/grafana/dynamic-table-queries.md b/documentation/cookbook/integrations/grafana/dynamic-table-queries.md
@@ -1,23 +1,23 @@
 ---
-title: Query Multiple Tables Dynamically in Grafana
+title: Query multiple tables dynamically in Grafana
 sidebar_label: Dynamic table queries
 description: Use Grafana variables to dynamically query multiple tables with the same schema for time-series visualization
 ---
 
 Query multiple QuestDB tables dynamically in Grafana using dashboard variables. This is useful when you have many tables with identical schemas (e.g., sensor data, metrics from different sources) and want to visualize them together without hardcoding table names in your queries.
 
-## Problem: Visualize Many Similar Tables
+## Problem: Visualize many similar tables
 
 You have 100+ tables with the same structure (e.g., `sensor_1`, `sensor_2`, ..., `sensor_n`) and want to:
 1. Display data from all tables on a single Grafana chart
 2. Avoid manually updating queries when tables are added or removed
 3. Allow users to select which tables to visualize via dashboard controls
 
-## Solution: Use Grafana Variables with Dynamic SQL
+## Solution: Use Grafana variables with dynamic SQL
 
 Create Grafana dashboard variables that query QuestDB for table names, then use string aggregation functions to build the SQL query dynamically.
 
-### Step 1: Get Table Names
+### Step 1: Get table names
 
 First, query QuestDB to get all relevant table names:
 
@@ -28,7 +28,7 @@ WHERE table_name LIKE 'sensor_%';
 
 This returns a list of all tables matching the pattern.
 
-### Step 2: Create Grafana Variables
+### Step 2: Create Grafana variables
 
 Create two dashboard variables to construct the dynamic query:
 
@@ -59,7 +59,7 @@ WHERE table_name LIKE 'sensor_%';
 
 This creates the column selection list with aggregation functions.
 
-### Step 3: Use Variables in Dashboard Query
+### Step 3: Use variables in dashboard query
 
 Now reference these variables in your Grafana chart query:
 
@@ -77,7 +77,7 @@ FROM sensor_1 ASOF JOIN sensor_2 ASOF JOIN sensor_3 ASOF JOIN sensor_4
 SAMPLE BY 1s FROM cast(1571176800000000 as timestamp) TO cast(1571349600000000 as timestamp) FILL(PREV);
 ```
 
-## How It Works
+## How it works
 
 The solution uses three key QuestDB features:
 
@@ -99,7 +99,7 @@ Combined with Grafana's variable interpolation:
 
 This ensures that even if tables update at different rates, you get a complete dataset with the most recent known value from each table.
 
-## Adapting the Pattern
+## Adapting the pattern
 
 **Filter by different patterns:**
 ```sql
@@ -114,7 +114,7 @@ WHERE table_name LIKE 'sensor_%'
   AND table_name NOT IN ('sensor_test', 'sensor_backup')
 ```
 
-## Programmatic Alternative
+## Programmatic alternative
 
 If you're not using Grafana, you can achieve the same result programmatically:
 
@@ -142,7 +142,7 @@ If you're not using Grafana, you can achieve the same result programmatically:
    """
    ```
 
-## Handling Different Sampling Intervals
+## Handling different sampling intervals
 
 When tables have different update frequencies, use FILL to handle gaps:
 

diff --git a/documentation/cookbook/integrations/grafana/overlay-timeshift.md b/documentation/cookbook/integrations/grafana/overlay-timeshift.md
@@ -1,5 +1,5 @@
 ---
-title: Overlay Two Time Series with Time Shift
+title: Overlay two time series with time shift
 sidebar_label: Overlay with timeshift
 description: Overlay yesterday's and today's data on the same Grafana chart using time shift
 ---

diff --git a/documentation/cookbook/integrations/grafana/read-only-user.md b/documentation/cookbook/integrations/grafana/read-only-user.md
@@ -1,5 +1,5 @@
 ---
-title: Configure Read-Only User for Grafana
+title: Configure read-only user for Grafana
 sidebar_label: Read-only user
 description: Set up a read-only PostgreSQL user for Grafana dashboards while maintaining admin access for DDL operations
 ---
@@ -10,7 +10,7 @@ Configure a dedicated read-only user for Grafana to improve security by preventi
 For QuestDB Enterprise, use the comprehensive [Role-Based Access Control (RBAC)](/docs/security/rbac/) system to create granular user permissions and roles. The configuration below applies to QuestDB Open Source.
 :::
 
-## Problem: Separate Read and Write Access
+## Problem: Separate read and write access
 
 You want to:
 1. Connect Grafana with read-only credentials
@@ -19,7 +19,7 @@ You want to:
 
 However, QuestDB's PostgreSQL wire protocol doesn't support standard PostgreSQL user management commands like `CREATE USER` or `GRANT`.
 
-## Solution: Enable the Read-Only User
+## Solution: Enable the read-only user
 
 QuestDB Open Source supports a built-in read-only user that can be enabled via configuration. This gives you two users:
 - **Admin user** (default: `admin`): Full access for DDL and DML operations
@@ -58,7 +58,7 @@ docker run \
   questdb/questdb:latest
 ```
 
-### Using the Read-Only User
+### Using the read-only user
 
 After enabling, you have two separate users: