{"id":6322,"date":"2019-01-24T12:04:52","date_gmt":"2019-01-24T20:04:52","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=6322"},"modified":"2025-06-13T20:19:53","modified_gmt":"2025-06-14T03:19:53","slug":"n1ql-to-query-or-to-analyze","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/","title":{"rendered":"N1QL: To Query or To Analyze?"},"content":{"rendered":"

Note: This recommendation note was written in collaboration with Till Westmann and Mike Carey, who lead the Couchbase analytics R&D.<\/p>\n

[Part 2 of this article by Even Pease is at: https:\/\/www.couchbase.com\/blog\/part-2-n1ql-to-query-or-to-analyze\/<\/a>]<\/p>\n

Couchbase’s Query and Analytics Services both support N1QL (SQL for JSON). \u00a0A common question is: \u201cWhich service should run my query?\u201d.\u00a0<\/span>The quick answer is: \u201cIt depends on your workload<\/a>\u201d. \u00a0This blog explains this answer.<\/span><\/p>\n

A transaction is when you buy coffee and cake at the grocery store.\u00a0<\/span>The analysis is when the grocery store looks at all the sales data to see what day of the week, what month of the year coffee and\/or cake sells more – so they can plan the inventory, sales, and prices.<\/span><\/p>\n

Every business does these three things in a cycle or a spiral [The Goal]. <\/span><\/p>\n

    \n
  1. Run the business process to deliver products or services to the customers.<\/span><\/li>\n
  2. Analyze the business to determine what to change and what to change to.<\/span><\/li>\n
  3. Make the change happen.<\/span><\/li>\n<\/ol>\n

    In modern day business, each step requires applications perform the steps.<\/span><\/p>\n

    \"\"<\/p>\n

    The Query Service is used by the applications needed to run the the business; it is designed for large number of concurrent queries, each doing small amount of work. \u00a0In the RDBMS world, this workload is called the OLTP workload. <\/span><\/p>\n

    Applications or tools used for analysis have different workload characteristics. \u00a0These typically use the Analytics Service; it is designed for a smaller number of concurrent queries analyzing a larger number of documents. In the RDBMS world, this workload is called the OLAP workload. \u00a0<\/span><\/p>\n

    Let\u2019s drill down into details into these two services.<\/span><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    Query Service<\/b><\/span><\/td>\nAnalytics Service<\/b><\/span><\/td>\n<\/tr>\n
    Tutorials<\/strong><\/span><\/td>\n<\/tr>\n
    https:\/\/query-tutorial.couchbase.com\/tutorial\/#1<\/span><\/a><\/td>\nhttps:\/\/sqlplusplus-tutorial.couchbase.com\/tutorial\/#1<\/span><\/a><\/td>\n<\/tr>\n
    High Level Comparison<\/strong><\/span><\/td>\n<\/tr>\n
    Used for data manipulation within application logic<\/span><\/td>\nUsed for reports, analysis (historical, interactive), dashboards<\/span><\/td>\n<\/tr>\n
    Short queries<\/span><\/p>\n

    \u00a0— Relatively simple SQL<\/span><\/p>\n

    \u00a0— Typically involving small amounts of data<\/span><\/td>\n

    		Longer operations<\/span><\/p>\n

    \u00a0— Complex SQL with analytics<\/span><\/p>\n

    \u00a0— Typically involving larger amounts of data<\/span><\/td>\n<\/tr>\n

    Run SELECT, INSERT, UPDATE, DELETE, MERGE for operational applications<\/span><\/td>\nRun SELECT for analysis<\/span><\/td>\n<\/tr>\n
    Random Updates<\/span><\/p>\n

    \u00a0— Update few documents per query<\/span><\/td>\n

    		No Updates<\/span><\/p>\n

    \u00a0— Changes ingested from Data Service<\/span><\/td>\n<\/tr>\n

    Millisecond to a second latency,<\/span><\/p>\n

    high throughput (10-1000 qps), performance goal is queries\/second<\/span><\/td>\n

    		Second to minutes response time,<\/span><\/p>\n

    <1-10 queries per second,<\/span><\/p>\n

    performance goal is seconds\/query<\/span><\/td>\n<\/tr>\n

    Large number of Indexes<\/span><\/td>\nFewer indexes<\/span><\/td>\n<\/tr>\n
    Developer written queries; generated queries are well known<\/span><\/td>\nAd-hoc queries; complex reports, dashboards, BI workload<\/span><\/td>\n<\/tr>\n
    Queries execute on a single query node using the distributed index and data infrastructure<\/span><\/td>\nQueries execute on all analytics nodes using its distributed compute, index and data infrastructure<\/span><\/td>\n<\/tr>\n
    Technical Comparison: Architecture<\/strong><\/span><\/td>\n<\/tr>\n
    Queries run in SMP mode, throughput is scalable by adding new query nodes<\/span><\/td>\nQueries run in MPP mode, can handle larger data or reduce query execution times by adding new analytics nodes<\/span><\/td>\n<\/tr>\n
    Technical Comparison: Optimizer<\/strong><\/span><\/td>\n<\/tr>\n
    Nested loop join by default<\/span><\/p>\n

    Hash join via query hint<\/span><\/td>\n

    		Parallel hash join by default,<\/span><\/p>\n

    (Index-)Nested loop join or broadcast join via query hint<\/span><\/td>\n<\/tr>\n

    Technical Comparison: Indexes<\/strong><\/span><\/td>\n<\/tr>\n
    Global secondary indexes<\/span><\/td>\nLocal secondary indexes (co-located with data partitions)<\/span><\/td>\n<\/tr>\n
    Uses Memory Optimized Indexes; standard secondary indexes (Plasma)<\/span><\/td>\nLog-structured Merge Tree (LSM) based secondary indexes<\/span><\/td>\n<\/tr>\n
    Support for both covered and non-covered index scans<\/span><\/td>\nNon-covered index scans<\/span><\/td>\n<\/tr>\n
    Can use full text index for queries (6.5)<\/span><\/td>\n<\/td>\n<\/tr>\n
    Technical Comparison: Execution<\/strong><\/span><\/td>\n<\/tr>\n
    Most queries are prepared once and executed many times<\/span><\/td>\nAd-hoc and exploratory queries<\/span><\/td>\n<\/tr>\n
    SDKs use the prepare-execute model based on a ad-hoc flag<\/span><\/td>\nSDKs offer ad-hoc and parameterized queries<\/span><\/td>\n<\/tr>\n
    Most operations are done in memory; only when an index scan returns large data is it written to the disk backfill<\/span><\/td>\nBounded-memory operations on large data (larger than cluster memory) with graceful spilling as needed<\/span><\/td>\n<\/tr>\n
    Single node query parallelism<\/span><\/td>\nMulti-node partitioned-parallel join, sort, aggregate, and grouped aggregate operators<\/span><\/td>\n<\/tr>\n
    Expects a single (possibly RAIDed) storage device<\/span><\/td>\nUn-RAIDed use of multiple storage devices<\/span><\/td>\n<\/tr>\n
    Performance isolation via covering indexes that support scan, grouping, and aggregation operations on Index Service nodes<\/span><\/td>\nPerformance isolation for all queries via shadowing of data on Analytics Service nodes<\/span><\/td>\n<\/tr>\n
    Technical Documentation<\/span><\/strong><\/td>\n<\/tr>\n
    https:\/\/docs.couchbase.com\/server\/6.0\/n1ql\/n1ql-language-reference\/index.html<\/span><\/a><\/td>\nhttps:\/\/docs.couchbase.com\/server\/6.0\/analytics\/introduction.html<\/span><\/a><\/td>\n<\/tr>\n
    Technical Information<\/strong><\/span><\/td>\n<\/tr>\n
    https:\/\/www.couchbase.com\/products\/n1ql<\/span><\/a><\/td>\nhttps:\/\/www.couchbase.com\/sqlplusplus<\/span><\/a><\/td>\n<\/tr>\n
    Technical Books<\/strong><\/span><\/td>\n<\/tr>\n
    https:\/\/www.couchbase.com\/blog\/a-guide-to-n1ql-features-in-couchbase-5-5-special-edition\/<\/span><\/a><\/td>\nhttps:\/\/resources.couchbase.com\/sql_tutorial<\/span><\/a><\/p>\n

    https:\/\/www.amazon.com\/SQL-Users-Tutorial-Don-Chamberlin\/dp\/0692184503\/<\/span><\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

     <\/p>\n

      \n
    1. [The GOAL]: The Goal: The process of ongoing improvement.\u00a0<\/span>https:\/\/www.amazon.com\/Goal-Process-Ongoing-Improvement\/dp\/0884271951\/ref=sr_1_1?keywords=the+goal&qid=1547969233&sr=8-1<\/a><\/li>\n
    2. Systems of Engagement for Customer Jobs: https:\/\/marketing.cioreview.com\/cxoinsight\/systems-of-engagement-for-customer-jobs-nid-24677-cid-51.html<\/a><\/li>\n
    3. Part 2 of this article by Even Pease: https:\/\/www.couchbase.com\/blog\/part-2-n1ql-to-query-or-to-analyze\/<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

      Note: This recommendation note was written in collaboration with Till Westmann and Mike Carey, who lead the Couchbase analytics R&D. [Part 2 of this article by Even Pease is at: https:\/\/www.couchbase.com\/blog\/part-2-n1ql-to-query-or-to-analyze\/] Couchbase’s Query and Analytics Services both support N1QL (SQL […]<\/p>\n","protected":false},"author":55,"featured_media":5959,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1815,2294,1816,9417,1812],"tags":[1261,1725,2297],"ppma_author":[8929],"class_list":["post-6322","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-best-practices-and-tutorials","category-analytics","category-couchbase-server","category-performance","category-n1ql-query","tag-json","tag-nosql-database","tag-workload"],"acf":[],"yoast_head":"\nN1QL: To Query or To Analyze? - The Couchbase Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"N1QL: To Query or To Analyze?\" \/>\n<meta property=\"og:description\" content=\"Note: This recommendation note was written in collaboration with Till Westmann and Mike Carey, who lead the Couchbase analytics R&D. [Part 2 of this article by Even Pease is at: https:\/\/www.couchbase.com\/blog\/part-2-n1ql-to-query-or-to-analyze\/] Couchbase’s Query and Analytics Services both support N1QL (SQL […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2019-01-24T20:04:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-06-14T03:19:53+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2018\/11\/Screen-Shot-2018-11-14-at-3.46.47-PM.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1212\" \/>\n\t<meta property=\"og:image:height\" content=\"748\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Keshav Murthy\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@rkeshavmurthy\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Keshav Murthy\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/\"},\"author\":{\"name\":\"Keshav Murthy\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/#\/schema\/person\/c261644262bf98e146372fe647682636\"},\"headline\":\"N1QL: To Query or To Analyze?\",\"datePublished\":\"2019-01-24T20:04:52+00:00\",\"dateModified\":\"2025-06-14T03:19:53+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/\"},\"wordCount\":794,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2018\/11\/Screen-Shot-2018-11-14-at-3.46.47-PM.png\",\"keywords\":[\"JSON\",\"NoSQL Database\",\"workload\"],\"articleSection\":[\"Best Practices and Tutorials\",\"Couchbase Analytics\",\"Couchbase Server\",\"High Performance\",\"SQL++ \/ N1QL Query\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/\",\"url\":\"https:\/\/www.couchbase.com\/blog\/n1ql-to-query-or-to-analyze\/\",\"name\":\"N1QL: To Query or To Analyze? 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