Graph Analytics

<h2 id="graph-analytics-in-geode" class="position-relative d-flex align-items-center group"> Graph Analytics in Geode <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="graph-analytics-in-geode" aria-haspopup="dialog" aria-label="Share link: Graph Analytics in Geode"> Share link </button> </h2><div id="headingShareModal" class="heading-share-modal" role="dialog" aria-modal="true" aria-labelledby="headingShareTitle" hidden> <div class="hsm-dialog" role="document"> <div class="hsm-header"> <h2 id="headingShareTitle" class="h6 mb-0 fw-bold">Share this section</h2> <button type="button" class="hsm-close" aria-label="Close"> </button> </div> <div class="hsm-body"> <label for="headingShareInput" class="form-label small text-muted mb-1 text-uppercase fw-bold" style="font-size: 0.7rem; letter-spacing: 0.5px;">Permalink</label> <div class="input-group mb-4 hsm-url-group"> <input id="headingShareInput" type="text" class="form-control font-monospace" readonly aria-readonly="true" style="font-size: 0.85rem;" /> <button class="btn btn-primary hsm-copy" type="button" aria-label="Copy" title="Copy"> </button> </div> <div class="small fw-bold mb-2 text-muted text-uppercase" style="font-size: 0.7rem; 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Geode’s implementation of the ISO/IEC 39075:2024 GQL standard provides powerful analytical capabilities for path analysis, centrality measurement, community detection, and business intelligence. <h3 id="why-graph-analytics" class="position-relative d-flex align-items-center group"> Why Graph Analytics? <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="why-graph-analytics" aria-haspopup="dialog" aria-label="Share link: Why Graph Analytics?"> Share link </button> </h3>Traditional relational databases excel at structured queries but struggle with relationship-heavy analytics. Graph databases like Geode naturally model and query connected data, enabling: <ul> <li>Relationship Discovery: Find hidden connections across multiple hops</li> <li>Pattern Recognition: Identify recurring structures in complex networks</li> <li>Influence Analysis: Measure node importance and information flow</li> <li>Community Detection: Discover clusters and groupings</li> <li>Anomaly Detection: Spot unusual patterns in connected data</li> </ul> <h3 id="core-analytical-capabilities" class="position-relative d-flex align-items-center group"> Core Analytical Capabilities <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="core-analytical-capabilities" aria-haspopup="dialog" aria-label="Share link: Core Analytical Capabilities"> Share link </button> </h3> <h4 id="path-analysis" class="position-relative d-flex align-items-center group"> Path Analysis <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="path-analysis" aria-haspopup="dialog" aria-label="Share link: Path Analysis"> Share link </button> </h4>Path queries reveal how nodes connect through relationship chains, essential for network analysis, recommendation systems, and logistics optimization. <h5 id="shortest-path-queries" class="position-relative d-flex align-items-center group"> Shortest Path Queries <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="shortest-path-queries" aria-haspopup="dialog" aria-label="Share link: Shortest Path Queries"> Share link </button> </h5>Find the most efficient route between two nodes: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Single shortest path MATCH path = SHORTEST (a:Person {name: 'Alice'})-[:KNOWS*]->(b:Person {name: 'Bob'}) RETURN path, length(path) AS hops; -- All shortest paths (when multiple exist) MATCH paths = ALL SHORTEST (a:City {name: 'San Francisco'}) -[:FLIGHT*]-> (b:City {name: 'New York'}) RETURN paths, [r IN relationships(paths) | r.airline] AS airlines, reduce(cost = 0, r IN relationships(paths) | cost + r.price) AS total_cost; </code></pre></div> <h5 id="k-shortest-paths" class="position-relative d-flex align-items-center group"> K-Shortest Paths <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="k-shortest-paths" aria-haspopup="dialog" aria-label="Share link: K-Shortest Paths"> Share link </button> </h5>Find multiple alternative paths: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Top 3 shortest paths with total distance MATCH paths = K SHORTEST 3 (start:Location {id: 'warehouse_1'}) -[:ROUTE*]-> (end:Location {id: 'customer_42'}) RETURN paths, reduce(dist = 0, r IN relationships(paths) | dist + r.distance) AS total_distance ORDER BY total_distance; </code></pre></div> <h5 id="path-filtering" class="position-relative d-flex align-items-center group"> Path Filtering <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="path-filtering" aria-haspopup="dialog" aria-label="Share link: Path Filtering"> Share link </button> </h5>Apply constraints on intermediate nodes or relationships: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find paths through active accounts only MATCH path = (sender:Account {id: $from}) -[:TRANSFER*2..5 (r, n | n.status = 'active' AND r.amount > 1000)]-> (receiver:Account {id: $to}) WHERE all(r IN relationships(path) WHERE r.timestamp >= DATE '2024-01-01') RETURN path; </code></pre></div> <h4 id="centrality-measures" class="position-relative d-flex align-items-center group"> Centrality Measures <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="centrality-measures" aria-haspopup="dialog" aria-label="Share link: Centrality Measures"> Share link </button> </h4>Centrality algorithms identify the most important nodes in a graph based on different criteria. <h5 id="degree-centrality" class="position-relative d-flex align-items-center group"> Degree Centrality <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="degree-centrality" aria-haspopup="dialog" aria-label="Share link: Degree Centrality"> Share link </button> </h5>Count of direct connections: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find most connected users MATCH (u:User) OPTIONAL MATCH (u)-[r:FOLLOWS]-() RETURN u.id, u.name, count(r) AS connections ORDER BY connections DESC LIMIT 20; -- In-degree vs out-degree MATCH (u:User) OPTIONAL MATCH (u)<-[:FOLLOWS]-(followers) OPTIONAL MATCH (u)-[:FOLLOWS]->(following) RETURN u.name, count(DISTINCT followers) AS follower_count, count(DISTINCT following) AS following_count, count(DISTINCT followers) * 1.0 / nullif(count(DISTINCT following), 0) AS follower_ratio ORDER BY follower_count DESC; </code></pre></div> <h5 id="betweenness-centrality" class="position-relative d-flex align-items-center group"> Betweenness Centrality <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="betweenness-centrality" aria-haspopup="dialog" aria-label="Share link: Betweenness Centrality"> Share link </button> </h5>Measures how often a node appears on shortest paths between other nodes (bridge/bottleneck detection): <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Identify key intermediaries in network MATCH (p:Person) CALL graph.betweenness_centrality(p, 'KNOWS') AS bc RETURN p.name, bc.score ORDER BY bc.score DESC LIMIT 10; </code></pre></div> <h5 id="pagerank-and-influence" class="position-relative d-flex align-items-center group"> PageRank and Influence <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="pagerank-and-influence" aria-haspopup="dialog" aria-label="Share link: PageRank and Influence"> Share link </button> </h5>Recursive importance based on connections from important nodes: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Calculate PageRank scores MATCH (page:WebPage) CALL graph.pagerank(page, 'LINKS_TO', { iterations: 20, damping: 0.85 }) AS pr RETURN page.url, pr.score ORDER BY pr.score DESC LIMIT 50; -- Social influence ranking MATCH (u:User) CALL graph.pagerank(u, 'FOLLOWS') AS influence WHERE influence.score > 0.01 RETURN u.name, influence.score, u.followers_count ORDER BY influence.score DESC; </code></pre></div> <h4 id="community-detection" class="position-relative d-flex align-items-center group"> Community Detection <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="community-detection" aria-haspopup="dialog" aria-label="Share link: Community Detection"> Share link </button> </h4>Identify clusters and groupings in your graph. <h5 id="label-propagation" class="position-relative d-flex align-items-center group"> Label Propagation <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="label-propagation" aria-haspopup="dialog" aria-label="Share link: Label Propagation"> Share link </button> </h5>Fast algorithm for community detection: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Detect communities in social network MATCH (u:User) CALL graph.label_propagation(u, 'FOLLOWS', 10) AS community RETURN community.id, collect(u.name) AS members, count(u) AS size ORDER BY size DESC; </code></pre></div> <h5 id="connected-components" class="position-relative d-flex align-items-center group"> Connected Components <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="connected-components" aria-haspopup="dialog" aria-label="Share link: Connected Components"> Share link </button> </h5>Find disconnected subgraphs: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Identify isolated clusters MATCH (n:Node) CALL graph.connected_components(n, 'CONNECTS') AS component RETURN component.id, count(n) AS size, collect(n.id) AS nodes HAVING size > 1 ORDER BY size DESC; </code></pre></div> <h5 id="modularity-based-clustering" class="position-relative d-flex align-items-center group"> Modularity-Based Clustering <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="modularity-based-clustering" aria-haspopup="dialog" aria-label="Share link: Modularity-Based Clustering"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- High-quality community detection MATCH (u:User) CALL graph.louvain(u, 'INTERACTS', { levels: 3, resolution: 1.0 }) AS cluster RETURN cluster.level, cluster.community_id, collect(u.name) AS members, count(u) AS size ORDER BY cluster.level, size DESC; </code></pre></div> <h4 id="pattern-matching-and-discovery" class="position-relative d-flex align-items-center group"> Pattern Matching and Discovery <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="pattern-matching-and-discovery" aria-haspopup="dialog" aria-label="Share link: Pattern Matching and Discovery"> Share link </button> </h4>GQL’s powerful pattern matching enables complex analytical queries. <h5 id="triangle-counting" class="position-relative d-flex align-items-center group"> Triangle Counting <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="triangle-counting" aria-haspopup="dialog" aria-label="Share link: Triangle Counting"> Share link </button> </h5>Measure clustering coefficient: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find triangles in social network MATCH (a:Person)-[:KNOWS]->(b:Person)-[:KNOWS]->(c:Person)-[:KNOWS]->(a) WHERE a.id < b.id AND b.id < c.id -- Avoid duplicates RETURN count(*) AS triangle_count; -- Triangles involving specific user MATCH (a:Person {name: 'Alice'})-[:KNOWS]->(b)-[:KNOWS]->(c)-[:KNOWS]->(a) RETURN DISTINCT b.name, c.name; </code></pre></div> <h5 id="cycle-detection" class="position-relative d-flex align-items-center group"> Cycle Detection <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="cycle-detection" aria-haspopup="dialog" aria-label="Share link: Cycle Detection"> Share link </button> </h5>Find circular dependencies or loops: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Detect circular dependencies in task graph MATCH path = (t:Task)-[:DEPENDS_ON*2..10]->(t) RETURN path, length(path) AS cycle_length ORDER BY cycle_length; </code></pre></div> <h5 id="motif-discovery" class="position-relative d-flex align-items-center group"> Motif Discovery <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="motif-discovery" aria-haspopup="dialog" aria-label="Share link: Motif Discovery"> Share link </button> </h5>Find specific subgraph patterns: <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find "star" pattern: one person followed by many MATCH (influencer:Person)<-[:FOLLOWS]-(followers:Person) WITH influencer, collect(followers) AS follower_list WHERE size(follower_list) > 100 RETURN influencer.name, size(follower_list) AS follower_count ORDER BY follower_count DESC; -- Find "bridge" pattern: users connecting different communities MATCH (a:Person)-[:KNOWS]->(bridge:Person)-[:KNOWS]->(b:Person) WHERE a.community_id <> b.community_id AND a.community_id <> bridge.community_id AND b.community_id <> bridge.community_id RETURN bridge.name, count(DISTINCT a.community_id) AS communities_bridged ORDER BY communities_bridged DESC; </code></pre></div> <h3 id="aggregations-and-statistics" class="position-relative d-flex align-items-center group"> Aggregations and Statistics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="aggregations-and-statistics" aria-haspopup="dialog" aria-label="Share link: Aggregations and Statistics"> Share link </button> </h3> <h4 id="basic-aggregations" class="position-relative d-flex align-items-center group"> Basic Aggregations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="basic-aggregations" aria-haspopup="dialog" aria-label="Share link: Basic Aggregations"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Sales analytics MATCH (p:Product)<-[:PURCHASED]-(u:User) RETURN p.category, count(u) AS total_purchases, count(DISTINCT u) AS unique_customers, avg(p.price) AS avg_price, sum(p.price) AS total_revenue GROUP BY p.category ORDER BY total_revenue DESC; </code></pre></div> <h4 id="statistical-functions" class="position-relative d-flex align-items-center group"> Statistical Functions <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="statistical-functions" aria-haspopup="dialog" aria-label="Share link: Statistical Functions"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Price distribution analysis MATCH (p:Product) WHERE p.category = 'Electronics' RETURN p.subcategory, count(*) AS product_count, avg(p.price) AS mean_price, stddev(p.price) AS price_stddev, percentile(p.price, 0.25) AS q1_price, percentile(p.price, 0.50) AS median_price, percentile(p.price, 0.75) AS q3_price, percentile(p.price, 0.95) AS p95_price, min(p.price) AS min_price, max(p.price) AS max_price GROUP BY p.subcategory; </code></pre></div> <h4 id="window-functions" class="position-relative d-flex align-items-center group"> Window Functions <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="window-functions" aria-haspopup="dialog" aria-label="Share link: Window Functions"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Rank products within categories MATCH (p:Product) RETURN p.category, p.name, p.sales, rank() OVER (PARTITION BY p.category ORDER BY p.sales DESC) AS rank_in_category, p.sales - avg(p.sales) OVER (PARTITION BY p.category) AS deviation_from_avg ORDER BY p.category, rank_in_category; </code></pre></div> <h3 id="time-series-analytics" class="position-relative d-flex align-items-center group"> Time-Series Analytics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="time-series-analytics" aria-haspopup="dialog" aria-label="Share link: Time-Series Analytics"> Share link </button> </h3>Geode’s temporal support enables time-based graph analysis. <h4 id="temporal-aggregations" class="position-relative d-flex align-items-center group"> Temporal Aggregations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="temporal-aggregations" aria-haspopup="dialog" aria-label="Share link: Temporal Aggregations"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Sales trends over time MATCH (s:Sale) WHERE s.timestamp >= DATE '2024-01-01' RETURN date_trunc('month', s.timestamp) AS month, count(*) AS sale_count, sum(s.amount) AS revenue, avg(s.amount) AS avg_order_value GROUP BY month ORDER BY month; </code></pre></div> <h4 id="temporal-pattern-analysis" class="position-relative d-flex align-items-center group"> Temporal Pattern Analysis <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="temporal-pattern-analysis" aria-haspopup="dialog" aria-label="Share link: Temporal Pattern Analysis"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- User activity patterns by day of week MATCH (u:User)-[:LOGGED_IN]->(session:Session) RETURN extract(dow from session.timestamp) AS day_of_week, extract(hour from session.timestamp) AS hour, count(*) AS session_count GROUP BY day_of_week, hour ORDER BY day_of_week, hour; </code></pre></div> <h4 id="change-detection" class="position-relative d-flex align-items-center group"> Change Detection <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="change-detection" aria-haspopup="dialog" aria-label="Share link: Change Detection"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Identify sudden spikes in activity WITH DATE '2024-01-01' AS start_date, DATE '2024-12-31' AS end_date MATCH (e:Event) WHERE e.timestamp >= start_date AND e.timestamp <= end_date WITH date_trunc('day', e.timestamp) AS day, count(*) AS daily_count WITH day, daily_count, avg(daily_count) OVER (ORDER BY day ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS moving_avg WHERE daily_count > moving_avg * 2 -- Spike: 2x the moving average RETURN day, daily_count, moving_avg ORDER BY day; </code></pre></div> <h3 id="real-time-analytics" class="position-relative d-flex align-items-center group"> Real-Time Analytics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="real-time-analytics" aria-haspopup="dialog" aria-label="Share link: Real-Time Analytics"> Share link </button> </h3> <h4 id="streaming-aggregations" class="position-relative d-flex align-items-center group"> Streaming Aggregations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="streaming-aggregations" aria-haspopup="dialog" aria-label="Share link: Streaming Aggregations"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Recent activity dashboard (last 15 minutes) MATCH (u:User)-[:ACTION]->(a:Action) WHERE a.timestamp >= CURRENT_TIMESTAMP - DURATION 'PT15M' RETURN a.type, count(*) AS action_count, count(DISTINCT u) AS unique_users, max(a.timestamp) AS last_occurrence GROUP BY a.type ORDER BY action_count DESC; </code></pre></div> <h4 id="live-monitoring" class="position-relative d-flex align-items-center group"> Live Monitoring <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="live-monitoring" aria-haspopup="dialog" aria-label="Share link: Live Monitoring"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Active sessions right now MATCH (u:User)-[:HAS_SESSION]->(s:Session) WHERE s.started <= CURRENT_TIMESTAMP AND (s.ended IS NULL OR s.ended >= CURRENT_TIMESTAMP) RETURN count(DISTINCT u) AS active_users, count(s) AS active_sessions; </code></pre></div> <h3 id="business-intelligence-use-cases" class="position-relative d-flex align-items-center group"> Business Intelligence Use Cases <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="business-intelligence-use-cases" aria-haspopup="dialog" aria-label="Share link: Business Intelligence Use Cases"> Share link </button> </h3> <h4 id="customer-analytics" class="position-relative d-flex align-items-center group"> Customer Analytics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="customer-analytics" aria-haspopup="dialog" aria-label="Share link: Customer Analytics"> Share link </button> </h4> <h5 id="customer-segmentation" class="position-relative d-flex align-items-center group"> Customer Segmentation <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="customer-segmentation" aria-haspopup="dialog" aria-label="Share link: Customer Segmentation"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- RFM analysis (Recency, Frequency, Monetary) MATCH (c:Customer)-[:MADE]->(o:Order) WITH c, max(o.date) AS last_order_date, count(o) AS order_count, sum(o.total) AS total_spent RETURN c.id, c.name, CURRENT_DATE - last_order_date AS days_since_last_order, order_count, total_spent, CASE WHEN days_since_last_order <= 30 AND total_spent > 1000 THEN 'VIP' WHEN days_since_last_order <= 90 AND order_count > 5 THEN 'Loyal' WHEN days_since_last_order > 180 THEN 'At Risk' ELSE 'Regular' END AS segment ORDER BY total_spent DESC; </code></pre></div> <h5 id="customer-lifetime-value" class="position-relative d-flex align-items-center group"> Customer Lifetime Value <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="customer-lifetime-value" aria-haspopup="dialog" aria-label="Share link: Customer Lifetime Value"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Calculate CLV projection MATCH (c:Customer)-[:MADE]->(o:Order) WITH c, count(o) AS order_count, sum(o.total) AS total_spent, avg(o.total) AS avg_order_value, min(o.date) AS first_order, max(o.date) AS last_order WITH c, order_count, total_spent, avg_order_value, (last_order - first_order) AS customer_age_days, (order_count * 1.0 / nullif((last_order - first_order), 0)) AS orders_per_day RETURN c.id, total_spent AS historical_value, avg_order_value * orders_per_day * 365 AS projected_annual_value, total_spent + (avg_order_value * orders_per_day * 365 * 3) AS projected_3yr_ltv ORDER BY projected_3yr_ltv DESC LIMIT 100; </code></pre></div> <h4 id="recommendation-analytics" class="position-relative d-flex align-items-center group"> Recommendation Analytics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="recommendation-analytics" aria-haspopup="dialog" aria-label="Share link: Recommendation Analytics"> Share link </button> </h4> <h5 id="collaborative-filtering" class="position-relative d-flex align-items-center group"> Collaborative Filtering <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="collaborative-filtering" aria-haspopup="dialog" aria-label="Share link: Collaborative Filtering"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find similar users based on purchase behavior MATCH (u1:User {id: $user_id})-[:PURCHASED]->(p:Product)<-[:PURCHASED]-(u2:User) WHERE u1 <> u2 WITH u2, count(DISTINCT p) AS common_products ORDER BY common_products DESC LIMIT 10 MATCH (u2)-[:PURCHASED]->(recommended:Product) WHERE NOT EXISTS { MATCH (u1)-[:PURCHASED]->(recommended) } RETURN recommended.name, count(u2) AS recommended_by, avg(recommended.rating) AS avg_rating GROUP BY recommended.name ORDER BY recommended_by DESC, avg_rating DESC LIMIT 20; </code></pre></div> <h5 id="content-based-recommendations" class="position-relative d-flex align-items-center group"> Content-Based Recommendations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="content-based-recommendations" aria-haspopup="dialog" aria-label="Share link: Content-Based Recommendations"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Recommend similar products MATCH (p:Product {id: $product_id}) MATCH (similar:Product) WHERE similar <> p AND similar.category = p.category AND abs(similar.price - p.price) < 50 OPTIONAL MATCH (similar)<-[:PURCHASED]-(u:User)-[:PURCHASED]->(p) RETURN similar.name, similar.price, count(u) AS also_bought_count, similar.rating ORDER BY also_bought_count DESC, similar.rating DESC LIMIT 10; </code></pre></div> <h4 id="fraud-detection" class="position-relative d-flex align-items-center group"> Fraud Detection <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="fraud-detection" aria-haspopup="dialog" aria-label="Share link: Fraud Detection"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Detect suspicious transaction patterns MATCH (a1:Account)-[t1:TRANSFER]->(a2:Account)-[t2:TRANSFER]->(a3:Account) WHERE t1.timestamp >= CURRENT_TIMESTAMP - DURATION 'PT1H' AND t2.timestamp > t1.timestamp AND t2.timestamp <= t1.timestamp + DURATION 'PT5M' AND t1.amount > 10000 AND t2.amount >= t1.amount * 0.9 RETURN a1.id AS source, a2.id AS intermediary, a3.id AS destination, t1.amount AS initial_amount, t2.amount AS transfer_amount, t2.timestamp - t1.timestamp AS time_diff ORDER BY initial_amount DESC; </code></pre></div> <h4 id="supply-chain-analytics" class="position-relative d-flex align-items-center group"> Supply Chain Analytics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="supply-chain-analytics" aria-haspopup="dialog" aria-label="Share link: Supply Chain Analytics"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Analyze supply chain dependencies MATCH path = (supplier:Company {type: 'supplier'}) -[:SUPPLIES*]-> (manufacturer:Company {type: 'manufacturer'}) -[:SHIPS_TO]-> (distributor:Company {type: 'distributor'}) RETURN supplier.name, manufacturer.name, distributor.name, length(path) AS supply_chain_length, reduce(time = 0, r IN relationships(path) | time + r.lead_time_days) AS total_lead_time ORDER BY total_lead_time DESC; </code></pre></div> <h3 id="performance-optimization-for-analytics" class="position-relative d-flex align-items-center group"> Performance Optimization for Analytics <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="performance-optimization-for-analytics" aria-haspopup="dialog" aria-label="Share link: Performance Optimization for Analytics"> Share link </button> </h3> <h4 id="index-strategy" class="position-relative d-flex align-items-center group"> Index Strategy <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="index-strategy" aria-haspopup="dialog" aria-label="Share link: Index Strategy"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create indexes for analytical queries CREATE INDEX user_timestamp ON User(last_active); CREATE INDEX product_category_price ON Product(category, price); CREATE INDEX order_customer_date ON Order(customer_id, order_date); </code></pre></div> <h4 id="query-profiling" class="position-relative d-flex align-items-center group"> Query Profiling <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="query-profiling" aria-haspopup="dialog" aria-label="Share link: Query Profiling"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Profile analytical query PROFILE MATCH (u:User)-[:PURCHASED]->(p:Product) WHERE p.category = 'Electronics' AND u.country = 'USA' RETURN p.subcategory, count(u) AS customers, sum(p.price) AS revenue GROUP BY p.subcategory; </code></pre></div> <h4 id="materialized-views" class="position-relative d-flex align-items-center group"> Materialized Views <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="materialized-views" aria-haspopup="dialog" aria-label="Share link: Materialized Views"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Pre-compute expensive analytics CREATE MATERIALIZED VIEW daily_sales_summary AS MATCH (o:Order) WHERE o.date >= CURRENT_DATE - DURATION 'P90D' RETURN date_trunc('day', o.date) AS day, o.region, count(*) AS order_count, sum(o.total) AS revenue, avg(o.total) AS avg_order_value GROUP BY day, o.region; -- Use materialized view MATCH (s:daily_sales_summary) WHERE s.region = 'West' AND s.day >= DATE '2024-01-01' RETURN s.day, s.revenue ORDER BY s.day; </code></pre></div> <h3 id="comparison-with-other-analytics-platforms" class="position-relative d-flex align-items-center group"> Comparison with Other Analytics Platforms <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="comparison-with-other-analytics-platforms" aria-haspopup="dialog" aria-label="Share link: Comparison with Other Analytics Platforms"> Share link </button> </h3> <h4 id="vs-traditional-olap" class="position-relative d-flex align-items-center group"> vs. Traditional OLAP <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="vs-traditional-olap" aria-haspopup="dialog" aria-label="Share link: vs. Traditional OLAP"> Share link </button> </h4><ul> <li>Relationship Analysis: Geode excels at multi-hop queries; OLAP struggles with joins</li> <li>Real-Time: Geode supports real-time analytics; OLAP typically batch-oriented</li> <li>Schema: Graph schema more flexible than star/snowflake schemas</li> </ul> <h4 id="vs-spark-graphx" class="position-relative d-flex align-items-center group"> vs. Spark GraphX <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="vs-spark-graphx" aria-haspopup="dialog" aria-label="Share link: vs. Spark GraphX"> Share link </button> </h4><ul> <li>Query Language: GQL (declarative) vs. Scala/Python (procedural)</li> <li>Latency: Geode optimized for low-latency queries; Spark for batch processing</li> <li>Integration: Geode native graph DB; Spark requires data loading</li> </ul> <h4 id="vs-neo4j" class="position-relative d-flex align-items-center group"> vs. Neo4j <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="vs-neo4j" aria-haspopup="dialog" aria-label="Share link: vs. Neo4j"> Share link </button> </h4><ul> <li>Standards: Geode GQL standard; Neo4j proprietary Cypher</li> <li>Performance: Similar for most analytics; Geode faster for distributed workloads</li> <li>Built-in Algorithms: Both support graph algorithms; different implementations</li> </ul> <h3 id="best-practices" class="position-relative d-flex align-items-center group"> Best Practices <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="best-practices" aria-haspopup="dialog" aria-label="Share link: Best Practices"> Share link </button> </h3><ol> <li>Index Frequently Filtered Properties: Speed up WHERE clauses</li> <li>Use LIMIT: Prevent excessive memory use in analytical queries</li> <li>Profile Before Optimizing: Identify actual bottlenecks</li> <li>Materialize Expensive Queries: Cache common analytics</li> <li>Batch Where Possible: Process historical analytics in batches</li> <li>Monitor Resource Usage: Graph analytics can be memory-intensive</li> </ol> <h3 id="getting-started" class="position-relative d-flex align-items-center group"> Getting Started <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="getting-started" aria-haspopup="dialog" aria-label="Share link: Getting Started"> Share link </button> </h3><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Import sample dataset CALL graph.load_sample('analytics_demo'); -- Run basic analytics MATCH (u:User)-[:PURCHASED]->(p:Product) RETURN p.category, count(u) AS customers ORDER BY customers DESC; -- Try path analysis MATCH path = SHORTEST (a:User)-[:KNOWS*]-(b:User) WHERE a.name = 'Alice' AND b.name = 'Bob' RETURN path; </code></pre></div>Explore the documentation below for detailed guides on specific analytical techniques, optimization strategies, and industry-specific use cases.

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