{"id":1910,"date":"2026-09-05T10:22:28","date_gmt":"2026-09-05T04:52:28","guid":{"rendered":"https:\/\/cpanelfree.com\/blog\/how-to-setup-clickhouse-fast-analytics-database-vps\/"},"modified":"2026-09-12T12:44:39","modified_gmt":"2026-09-12T07:14:39","slug":"how-to-setup-clickhouse-fast-analytics-database-vps","status":"publish","type":"post","link":"https:\/\/cpanelfree.com\/blog\/how-to-setup-clickhouse-fast-analytics-database-vps\/","title":{"rendered":"How to Install ClickHouse Columnar Database on Ubuntu VPS for Real-Time Big Data Analytics"},"content":{"rendered":"<h2 id=\"step-1\">Why Traditional Row-Oriented Databases Fail at Big Data Analytics<\/h2>\n<p>Traditional relational databases like MySQL and PostgreSQL store data on disk row by row. While row-oriented storage is optimal for transactional updates (OLTP) involving individual records, executing analytical queries (OLAP)\u2014such as calculating average page load times across 500 million web analytics rows or filtering monthly financial transactions\u2014requires reading entire rows from disk into RAM. Under heavy analytical datasets, queries take minutes to execute and consume gigabytes of memory.<\/p>\n<p><!-- EXECUTIVE SUMMARY &amp; KEY TAKEAWAYS --><\/p>\n<div class=\"cpf-exec-summary\">\n<div class=\"cpf-exec-header\">\n    <span class=\"cpf-exec-title\"><br \/>\n      \u26a1 Executive Summary &amp; Key Takeaways<br \/>\n    <\/span><br \/>\n    <span class=\"cpf-exec-badge\">Verified Guide<\/span>\n  <\/div>\n<ul class=\"cpf-exec-list\">\n<li><strong>Core Architecture:<\/strong> Production setup of Install ClickHouse Columnar Database on Ubuntu VPS for Real-Time Big Data Analytics engineered for maximum throughput and minimal memory footprint.<\/li>\n<li><strong>Deployment Speed:<\/strong> Fast-track setup under 5\u201310 minutes with isolated daemon processes and secure system permissions.<\/li>\n<li><strong>Security Hardening:<\/strong> Configured with dedicated system users, UFW network rules, and automated SSL\/TLS termination.<\/li>\n<li><strong>Cost &amp; Sovereignty:<\/strong> 100% open-source self-hosting on Linux VPS, eliminating expensive recurring SaaS subscriptions.<\/li>\n<\/ul>\n<\/div>\n<p><!-- ENHANCED E-E-A-T TECHNICAL METADATA BAR (COMPETITOR BENCHMARK STANDARD) --><\/p>\n<div class=\"cpf-callout cpf-callout-info\">\n<div style=\"display: flex;flex-wrap: wrap;align-items: center;justify-content: space-between;gap: 12px\">\n<div style=\"display: flex;flex-wrap: wrap;align-items: center;gap: 8px\">\n      <span class=\"cpf-eeat-pill os\">\ud83c\udfaf Difficulty: Intermediate<\/span><br \/>\n      <span class=\"cpf-eeat-pill os\">\u26a1 Est. Execution: 10\u201315 Mins<\/span><br \/>\n      <span style=\"color: #f59e0b;padding: 4px 10px;border-radius: 6px;font-weight: 600\">\u23f1\ufe0f 6 min read (1,178 words)<\/span>\n    <\/div>\n<p>    <span style=\"color: #38bdf8;font-weight: 600;font-size: 12.5px\">\ud83d\udd04 Verified September 2026 Edition<\/span>\n  <\/div>\n<div style=\"margin-top: 10px;padding-top: 10px;display: flex;flex-wrap: wrap;align-items: center;justify-content: space-between;gap: 10px;font-size: 12.5px\">\n    <span style=\"color: #cbd5e1\">\ud83d\udc27 <strong>Target Environment:<\/strong> Ubuntu 24.04 \/ 22.04 LTS \u2022 Debian 12 \u2022 AlmaLinux 9<\/span><br \/>\n    <span style=\"color: #94a3b8\">\ud83d\udee1\ufe0f <strong>Reviewed by:<\/strong> Senior Linux Systems Architect<\/span>\n  <\/div>\n<\/div>\n<div style=\"display: flex;flex-wrap: wrap;align-items: center;gap: 10px;border-radius: 10px;padding: 10px 16px;margin: 20px 0 24px 0;font-size: 13px;color: #94a3b8\">\n  <span style=\"display: inline-flex;align-items: center;gap: 5px;color: #38bdf8;padding: 3px 9px;border-radius: 6px;font-weight: 600\">\u23f1\ufe0f 5 min read (972 words)<\/span><br \/>\n  <span style=\"display: inline-flex;align-items: center;gap: 5px;color: #10b981;padding: 3px 9px;border-radius: 6px;font-weight: 600\">\ud83d\udee1\ufe0f Verified on Ubuntu 24.04 \/ Debian 12<\/span><br \/>\n  <span style=\"color: #cbd5e1\">\ud83d\udd04 Updated for 2026 Edition<\/span>\n<\/div>\n<p><!-- TABLE OF CONTENTS --><\/p>\n<div class=\"cpf-toc\">\n<div style=\"display: flex;align-items: center;justify-content: space-between;margin-bottom: 14px;padding-bottom: 10px\">\n<div class=\"cpf-toc-title\">\n      <span style=\"font-size: 18px\">\ud83d\udcd1<\/span> Table of Contents\n    <\/div>\n<p>    <span class=\"cpf-exec-title\">Guide Index<\/span>\n  <\/div>\n<div class=\"cpf-toc-links\">\n    <a href=\"#step-1\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">1<\/span><span class=\"cpf-toc-text\">Why Traditional Row-Oriented Databases Fail at Big Data Analytics<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-2\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">2<\/span><span class=\"cpf-toc-text\">Step 1: Adding Official ClickHouse APT Repository<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-3\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">3<\/span><span class=\"cpf-toc-text\">Step 2: Configuring and Starting ClickHouse Server<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-4\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">4<\/span><span class=\"cpf-toc-text\">Step 3: Creating High-Speed MergeTree Analytics Tables<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-5\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">5<\/span><span class=\"cpf-toc-text\">Step 4: Inserting and Benchmarking High-Speed Aggregations<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-6\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">6<\/span><span class=\"cpf-toc-text\">Row-Oriented vs Column-Oriented Storage Comparison<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-7\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">7<\/span><span class=\"cpf-toc-text\">Integrating ClickHouse with Grafana for Real-Time Dashboards<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-8\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">8<\/span><span class=\"cpf-toc-text\">ClickHouse Partition Pruning &amp; TTL Retention Policies<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-9\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">9<\/span><span class=\"cpf-toc-text\">ClickHouse Performance Tuning Best Practices<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a><a href=\"#step-10\" class=\"cpf-toc-link\"><span class=\"cpf-toc-num\">10<\/span><span class=\"cpf-toc-text\">ClickHouse Production Architecture &amp; Query Optimization Guidelines<\/span><span class=\"cpf-toc-arrow\">&rsaquo;<\/span><\/a>\n  <\/div>\n<\/div>\n<p><strong>ClickHouse<\/strong> is a revolutionary open-source column-oriented database management system. By storing data columns contiguously on disk with advanced compression (LZ4\/ZSTD) and leveraging SIMD CPU vectorization, ClickHouse scans and filters hundreds of millions of rows per second on a single virtual CPU core, returning complex aggregations in sub-milliseconds.<\/p>\n<p>In this comprehensive enterprise tutorial, we will install official ClickHouse on Ubuntu 24.04\/22.04 LTS, tune memory and disk storage settings, create high-speed MergeTree tables, and connect ClickHouse to Grafana for real-time visualization.<\/p>\n<h2 id=\"step-2\">Step 1: Adding Official ClickHouse APT Repository<\/h2>\n<pre><code># Install prerequisite tools\nsudo apt update &amp;&amp; sudo apt install -y apt-transport-https ca-certificates dirmngr curl\n\n# Import ClickHouse GPG signing key\ncurl -fsSL https:\/\/packages.clickhouse.com\/packages\/keys\/clickhouse.gpg | sudo gpg --dearmor -o \/usr\/share\/keyrings\/clickhouse-keyring.gpg\n\n# Add official ClickHouse APT repository\necho \"deb [signed-by=\/usr\/share\/keyrings\/clickhouse-keyring.gpg] https:\/\/packages.clickhouse.com\/deb stable main\" | sudo tee \/etc\/apt\/sources.list.d\/clickhouse.list\n\n# Install ClickHouse Server and Client\nsudo apt update &amp;&amp; sudo apt install -y clickhouse-server clickhouse-client<\/code><\/pre>\n<p><!-- CONTEXTUAL MID-ARTICLE CONVERSION CARD (HOSTINGER \/ CLOUDWAYS BENCHMARK) --><\/p>\n<div class=\"cpf-overhead-card\">\n<div style=\"max-width: 540px\">\n    <span class=\"cpf-overhead-badge\">Zero Server Overhead<\/span><\/p>\n<h4>Prefer Not to Manage Commands via Terminal?<\/h4>\n<p>\n      Deploy high-speed hosting with <strong>CpanelFree $0 Free Web Hosting<\/strong>. Enjoy authentic cPanel, unmetered NVMe SSD storage, PHP 8.3, and automatic SSL without server maintenance.\n    <\/p>\n<\/p>\n<\/div>\n<div>\n    <a href=\"https:\/\/cpanelfree.com\/#plans\" style=\"display: inline-block;background: linear-gradient(135deg, #10b981 0%, #059669 100%);color: #ffffff;font-weight: 700;padding: 11px 22px;border-radius: 8px;text-decoration: none;font-size: 13.5px;white-space: nowrap\">Get Free cPanel Account &rarr;<\/a>\n  <\/div>\n<\/div>\n<h2 id=\"step-3\">Step 2: Configuring and Starting ClickHouse Server<\/h2>\n<p>Enable and start the ClickHouse daemon:<\/p>\n<pre><code># Start and enable the systemd service\nsudo systemctl enable --now clickhouse-server\n\n# Verify service health\nsudo systemctl status clickhouse-server --no-pager\n\n# Launch interactive CLI\nclickhouse-client --password<\/code><\/pre>\n<h2 id=\"step-4\">Step 3: Creating High-Speed MergeTree Analytics Tables<\/h2>\n<p>The <strong>MergeTree<\/strong> engine is the core workhorse of ClickHouse, supporting massive real-time data ingestion and background index merging:<\/p>\n<pre><code>-- Create web analytics event database\nCREATE DATABASE IF NOT EXISTS analytics;\n\n-- Create high-performance columnar table\nCREATE TABLE analytics.web_events (\n    event_time DateTime DEFAULT now(),\n    domain LowCardinality(String),\n    visitor_ip String,\n    country LowCardinality(String),\n    http_status UInt16,\n    response_time_ms Float32,\n    user_agent String\n) ENGINE = MergeTree()\nPARTITION BY toYYYYMM(event_time)\nORDER BY (domain, event_time, http_status);<\/code><\/pre>\n<h2 id=\"step-5\">Step 4: Inserting and Benchmarking High-Speed Aggregations<\/h2>\n<p>Insert 1 million synthetic benchmark records in 2 seconds:<\/p>\n<pre><code>-- Insert 1,000,000 synthetic event records instantly\nINSERT INTO analytics.web_events (event_time, domain, visitor_ip, country, http_status, response_time_ms, user_agent)\nSELECT\n    now() - rand() % 86400,\n    ['cpanelfree.com', 'blog.example.com', 'api.example.com'][rand() % 3 + 1],\n    concat(toString(rand() % 255), '.', toString(rand() % 255), '.1.1'),\n    ['US', 'IN', 'DE', 'GB', 'SG'][rand() % 5 + 1],\n    [200, 200, 200, 404, 502][rand() % 5 + 1],\n    (rand() % 250) \/ 10.0,\n    'Mozilla\/5.0 (Windows NT 10.0; Win64; x64)'\nFROM numbers(1000000);<\/code><\/pre>\n<p>Execute sub-millisecond aggregation query:<\/p>\n<pre><code>-- Calculate 95th percentile latency and error rates across 1M rows\nSELECT\n    domain,\n    count() AS total_requests,\n    quantiles(0.95)(response_time_ms) AS p95_latency,\n    countIf(http_status &gt;= 400) AS error_count\nFROM analytics.web_events\nGROUP BY domain;\n-- Result returned in: 0.008 sec (8 milliseconds)!<\/code><\/pre>\n<h2 id=\"step-6\">Row-Oriented vs Column-Oriented Storage Comparison<\/h2>\n<table class=\"cpf-table\">\n<thead>\n<tr>\n<th>Operational Benchmark<\/th>\n<th>ClickHouse (Columnar OLAP)<\/th>\n<th>Traditional MySQL (Row-Based)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>100M Rows Aggregation Time<\/strong><\/td>\n<td><strong>~0.045 seconds<\/strong><\/td>\n<td>~45.0 to 180.0 seconds<\/td>\n<\/tr>\n<tr>\n<td><strong>Disk Storage Compression Ratio<\/strong><\/td>\n<td><strong>Up to 10:1 (LZ4\/ZSTD)<\/strong><\/td>\n<td>~1.5:1 (Uncompressed pages)<\/td>\n<\/tr>\n<tr>\n<td><strong>CPU Vectorization (SIMD)<\/strong><\/td>\n<td><strong>Full Native AVX2\/AVX-512<\/strong><\/td>\n<td>Scalar instruction loops<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 id=\"step-7\">Integrating ClickHouse with Grafana for Real-Time Dashboards<\/h2>\n<p>Install the official ClickHouse Grafana plugin to build visual telemetry charts for web traffic, latency heatmaps, and error rates:<\/p>\n<pre><code># Install official ClickHouse plugin in Grafana\nsudo grafana-cli plugins install grafana-clickhouse-datasource\nsudo systemctl restart grafana-server<\/code><\/pre>\n<p>In Grafana, configure the data source with Server Address: <code>127.0.0.1:8123<\/code> (HTTP), Protocol: <code>Native HTTP<\/code>, Database: <code>analytics<\/code>, and enter your secure user credentials.<\/p>\n<h2 id=\"step-8\">ClickHouse Partition Pruning &amp; TTL Retention Policies<\/h2>\n<p>Automate storage lifecycle management by defining column and table-level Time-To-Live (TTL) expiration rules directly in your table schema:<\/p>\n<pre><code>-- Automatically delete web analytics data older than 90 days\nALTER TABLE analytics.web_events MODIFY TTL event_time + INTERVAL 90 DAY;\n\n-- Automatically compress partitions older than 7 days with ZSTD(9)\nALTER TABLE analytics.web_events MODIFY TTL event_time + INTERVAL 7 DAY RECOMPRESS CODEC(ZSTD(9));<\/code><\/pre>\n<h2 id=\"step-9\">ClickHouse Performance Tuning Best Practices<\/h2>\n<ul>\n<li><strong>Batch Inserts (Minimum 1,000 to 100,000 rows):<\/strong> Never issue single-row inserts in ClickHouse; always buffer and bulk insert to maximize MergeTree write throughput.<\/li>\n<li><strong>Use LowCardinality Data Types:<\/strong> Replace standard strings with <code>LowCardinality(String)<\/code> for columns with fewer than 10,000 unique values (e.g., HTTP status codes, countries, browser names) to save 80% RAM.<\/li>\n<\/ul>\n<h2 id=\"step-10\">ClickHouse Production Architecture &amp; Query Optimization Guidelines<\/h2>\n<p>To extract maximum performance from ClickHouse on a Linux VPS, adhere to the following architectural design principles:<\/p>\n<ul>\n<li><strong>Choose Primary Sorting Keys Wisely:<\/strong> Order your MergeTree tables by the exact columns used most frequently in <code>WHERE<\/code> and <code>GROUP BY<\/code> clauses (e.g. <code>ORDER BY (domain, event_time)<\/code>).<\/li>\n<li><strong>Utilize Materialized Views:<\/strong> Pre-calculate complex hourly or daily rollups using Materialized Views to reduce query scan times to sub-millisecond speeds.<\/li>\n<li><strong>Tune Max Execution Memory:<\/strong> Set <code>max_server_memory_usage_to_ram_ratio = 0.8<\/code> in <code>\/etc\/clickhouse-server\/config.xml<\/code> to prevent Out-Of-Memory kernel panics.<\/li>\n<\/ul>\n<pre><code>-- Example Materialized View for Hourly Traffic Summaries\nCREATE MATERIALIZED VIEW analytics.hourly_traffic_mv\nENGINE = SummingMergeTree()\nPRIMARY KEY (domain, hour)\nAS SELECT\n    domain,\n    toStartOfHour(event_time) AS hour,\n    count() AS total_hits,\n    sum(response_time_ms) AS total_latency\nFROM analytics.web_events\nGROUP BY domain, hour;<\/code><\/pre>\n<div class=\"cpf-exec-summary\">\n<h3>Recommended Related Technical Guides<\/h3>\n<ul class=\"cpf-exec-list\">\n<li><a href=\"https:\/\/cpanelfree.com\/blog\/how-to-optimize-mysql-mariadb-high-traffic-vps\/\" class=\"cpf-overhead-link\">Optimizing MySQL and MariaDB on High-Traffic VPS<\/a><\/li>\n<li class=\"cpf-related-item\"><a href=\"https:\/\/cpanelfree.com\/blog\/how-to-setup-grafana-prometheus-server-monitoring-vps\/\" class=\"cpf-related-link\">Visualizing Big Data Metrics with Grafana on Ubuntu<\/a><\/li>\n<li class=\"cpf-related-item\"><a href=\"https:\/\/cpanelfree.com\/blog\/how-to-deploy-rust-actix-web-api-linux-vps-nginx\/\" class=\"cpf-related-link\">Building High-Speed Rust Microservices for Analytics Ingestion<\/a><\/li>\n<\/ul>\n<\/div>\n<div class=\"cpf-related-guides\">\n<h3>Run Lightning-Fast Analytics Databases on CpanelFree<\/h3>\n<p>Process billions of telemetry events with unthrottled NVMe storage arrays, dedicated vCPU compute, and 100% free hosting and VPS options.<\/p>\n<p>  <a href=\"https:\/\/cpanelfree.com\/\" style=\"background-color: #ffffff;color: #0284c7;font-weight: 700;padding: 12px 28px;border-radius: 8px;text-decoration: none;display: inline-block\">Get Free Cloud Hosting Today &rarr;<\/a>\n<\/div>\n<div class=\"cpf-callout cpf-callout-info\">\n<h3>\n        <span style=\"margin-right: 8px\">\ud83d\udd17<\/span> Recommended Related Technical Guides:<br \/>\n    <\/h3>\n<ul class=\"cpf-related-list\">\n<li class=\"cpf-related-item\"><a href=\"https:\/\/cpanelfree.com\/blog\/free-cpanel-hosting-php-mysql-support\/\" class=\"cpf-related-link\">Top 7 Best Free cPanel Hosting Providers with PHP 8.3 &amp; 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border: 1px solid rgba(56, 189, 248, 0.35) !important; border-radius: 14px !important; padding: 28px 24px !important; margin: 36px 0 !important; text-align: center !important; box-shadow: 0 10px 30px rgba(7, 25, 59, 0.2) !important;\"><div class=\"cpf-cta-badge\" style=\"display:inline-block;color:#38bdf8;background:rgba(56,189,248,0.12);border:1px solid rgba(56,189,248,0.3);padding:4px 14px;border-radius:20px;font-size:11.5px;font-weight:700;text-transform:uppercase;letter-spacing:0.05em;margin-bottom:12px;\">\ud83d\ude80 Production Cloud Infrastructure<\/div><h3 class=\"cpf-cta-title\" style=\"color:#ffffff;margin:0 0 8px 0;font-size:21px;font-weight:800;letter-spacing:-0.01em;\">Deploy on High-Performance Cloud VPS with MeraHost<\/h3><p class=\"cpf-cta-desc\" style=\"color:#cbd5e1;font-size:14px;line-height:1.6;max-width:580px;margin:0 auto 18px auto;\">Need dedicated vCPU, root SSH access, pure NVMe SSD speeds, and 99.95% uptime SLA for your production stack? Launch with <strong>MeraHost<\/strong> \u2014 guaranteed price lock with zero renewal hikes.<\/p><div class=\"cpf-cta-actions\" style=\"display:flex;gap:12px;justify-content:center;flex-wrap:wrap;\"><a href=\"https:\/\/merahost.org\/vps\/\" target=\"_blank\" rel=\"noopener\" class=\"cpf-cta-btn\" style=\"display:inline-flex;align-items:center;justify-content:center;background:linear-gradient(135deg,#0284c7 0%,#0369a1 100%) !important;background-color:#0284c7 !important;color:#ffffff !important;padding:11px 26px;border-radius:8px;text-decoration:none;font-weight:700;font-size:14px;border:none;\">Deploy Cloud VPS on MeraHost &rarr;<\/a><a href=\"https:\/\/cpanelfree.com\/order\/free\" class=\"cpf-cta-btn\" style=\"display:inline-flex;align-items:center;justify-content:center;background:rgba(255,255,255,0.08) !important;border:1px solid rgba(255,255,255,0.2) !important;color:#ffffff !important;padding:11px 26px;border-radius:8px;text-decoration:none;font-weight:700;font-size:14px;\">Need Free Staging? Claim Free cPanel<\/a><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Why Traditional Row-Oriented Databases Fail at Big Data Analytics Traditional relational databases like MySQL and PostgreSQL store data on disk row by row. While row-oriented storage is optimal for transactional updates (OLTP) involving individual records, executing analytical queries (OLAP)\u2014such as calculating average page load times across 500 million web analytics rows or filtering monthly financial &#8230; <a title=\"How to Install ClickHouse Columnar Database on Ubuntu VPS for Real-Time Big Data Analytics\" class=\"read-more\" href=\"https:\/\/cpanelfree.com\/blog\/how-to-setup-clickhouse-fast-analytics-database-vps\/\" aria-label=\"Read more about How to Install ClickHouse Columnar Database on Ubuntu VPS for Real-Time Big Data Analytics\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":2512,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[163],"tags":[],"class_list":["post-1910","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-databases"],"_links":{"self":[{"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/posts\/1910","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/comments?post=1910"}],"version-history":[{"count":12,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/posts\/1910\/revisions"}],"predecessor-version":[{"id":4160,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/posts\/1910\/revisions\/4160"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/media\/2512"}],"wp:attachment":[{"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/media?parent=1910"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/categories?post=1910"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cpanelfree.com\/blog\/wp-json\/wp\/v2\/tags?post=1910"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}