{"id":160,"date":"2020-11-29T09:22:38","date_gmt":"2020-11-29T08:22:38","guid":{"rendered":"https:\/\/ptdb.ch\/?p=160"},"modified":"2020-11-29T09:22:38","modified_gmt":"2020-11-29T08:22:38","slug":"postgresql-fillfactor-100-90-oracle-fillfactor-90-100-aka-pctfree","status":"publish","type":"post","link":"https:\/\/ptdb.ch\/?p=160","title":{"rendered":"PostgreSQL Fillfactor 100%\/90% &#8211; Oracle Fillfactor 90%\/100% (aka PCTFREE)"},"content":{"rendered":"<p>It is very interesting that Oracle and PostgreSQL are going in different directions when it comes to the fillfactor. It probably has to do with the different implementation of MVCC. I am not arguing that the one or the other is better, it is just very interesting to know that they are different. So what are the defaults?<\/p>\n<ul>\n<li>The fillfactor for PostgreSQL is\n<ul>\n<li>100% for tables<\/li>\n<li>90% for indexes<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li>The fillfactor for Oracle is\n<ul>\n<li>90% for tables<\/li>\n<li>100% for indexes<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>But why is this relevant to me? Most of the PostgreSQL Users out there will not notice this detail whatsoever. However, if you have tables with a huge update count, you might notice a big difference. Below I will show you the impact of the fillfactor in PostgreSQL. In case you want to know more about the different implementations, check out the docs on their websites.<\/p>\n<h3>Oracle PCTFREE<\/h3>\n<p>The default value is 10. This value reserves 10% of each block for updates to existing rows and allows inserts of new rows to fill a maximum of 90% of each block.<\/p>\n<p><a href=\"https:\/\/docs.oracle.com\/en\/database\/oracle\/oracle-database\/19\/sqlrf\/physical_attributes_clause.html#GUID-A15063A9-3237-43D3-B0AE-D01F6E80B393\">https:\/\/docs.oracle.com\/en\/database\/oracle\/oracle-database\/19\/sqlrf\/physical_attributes_clause.html#GUID-A15063A9-3237-43D3-B0AE-D01F6E80B393<\/a><\/p>\n<h3>PostgreSQL Fillfactor<\/h3>\n<p><a href=\"https:\/\/www.postgresql.org\/docs\/current\/sql-createtable.html\">https:\/\/www.postgresql.org\/docs\/current\/sql-createtable.html<\/a><\/p>\n<p>The fillfactor for a table is a percentage between 10 and 100. 100 (complete packing) is the default. When a smaller fillfactor is specified, INSERT operations pack table pages only to the indicated percentage; the remaining space on each page is reserved for updating rows on that page.<br \/>\nThis gives UPDATE a chance to place the updated copy of a row on the same page as the original, which is more efficient than placing it on a different page. For a table whose entries are never updated, complete packing is the best choice, but in heavily updated tables smaller fillfactors are appropriate. This parameter cannot be set for TOAST tables.<\/p>\n<p>Here is a little test case that shows that in PostgreSQL the fillfactor is really 100% for tables and 90% for indexes.<\/p>\n<p>Lets create a little test database first<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;postgres]&gt; create database fill;\nCREATE DATABASE\n(postgres@&#x5B;local]:55001)&#x5B;postgres]&gt; \\c fill\nYou are now connected to database &quot;fill&quot; as user &quot;postgres&quot;.\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt;\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt;\n<\/pre>\n<p>Now lets check out the table fillfactor, by creating two tables. One named t_fill_75 and the other named t_fill_100, and insert some test data into it.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; create table t_fill_75 ( a int, b text ) with ( fillfactor = 75 );\nCREATE TABLE\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; create table t_fill_100 ( a int, b text );\nCREATE TABLE\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\d+ t_fill_75\n                                 Table &quot;public.t_fill_75&quot;\n Column |  Type   | Collation | Nullable | Default | Storage  | Stats target | Description\n--------+---------+-----------+----------+---------+----------+--------------+-------------\n a      | integer |           |          |         | plain    |              |\n b      | text    |           |          |         | extended |              |\nAccess method: heap\nOptions: fillfactor=75\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\d+ t_fill_100\n                                 Table &quot;public.t_fill_100&quot;\n Column |  Type   | Collation | Nullable | Default | Storage  | Stats target | Description\n--------+---------+-----------+----------+---------+----------+--------------+-------------\n a      | integer |           |          |         | plain    |              |\n b      | text    |           |          |         | extended |              |\nAccess method: heap\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; insert into t_fill_75 select x, md5(x::text) from generate_series(1,1000) x;\nINSERT 0 1000\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; insert into t_fill_100 select x, md5(x::text) from generate_series(1,1000) x;\nINSERT 0 1000\n<\/pre>\n<p>As expected, the table t_fill_75 is slightly bigger, because the table is filled only up to 75%.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select pg_relation_size('t_fill_75');\n pg_relation_size\n------------------\n            98304\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select pg_relation_size('t_fill_100');\n pg_relation_size\n------------------\n            73728\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select relname, relpages, reltuples, (reltuples\/relpages)::int avgtuplperpage\n&gt; from pg_class where relname in ('t_fill_75','t_fill_100');\n  relname   | relpages | reltuples | avgtuplperpage\n------------+----------+-----------+----------------\n t_fill_75  |       12 |      1000 |             83\n t_fill_100 |        9 |      1000 |            111\n(2 rows)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select ctid, * from t_fill_75 where a &lt; 6;\n ctid  | a |                b\n-------+---+----------------------------------\n (0,1) | 1 | c4ca4238a0b923820dcc509a6f75849b\n (0,2) | 2 | c81e728d9d4c2f636f067f89cc14862c\n (0,3) | 3 | eccbc87e4b5ce2fe28308fd9f2a7baf3\n (0,4) | 4 | a87ff679a2f3e71d9181a67b7542122c\n (0,5) | 5 | e4da3b7fbbce2345d7772b0674a318d5\n(5 rows)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select ctid, * from t_fill_100 where a &lt; 6;\n ctid  | a |                b\n-------+---+----------------------------------\n (0,1) | 1 | c4ca4238a0b923820dcc509a6f75849b\n (0,2) | 2 | c81e728d9d4c2f636f067f89cc14862c\n (0,3) | 3 | eccbc87e4b5ce2fe28308fd9f2a7baf3\n (0,4) | 4 | a87ff679a2f3e71d9181a67b7542122c\n (0,5) | 5 | e4da3b7fbbce2345d7772b0674a318d5\n(5 rows)\n\n<\/pre>\n<p>When we start updating the tables it becomes interesting. You can see clearly that in table t_fill_100 one row is in a different block.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; update t_fill_75 set b = 'dummy' where a = 2;\nUPDATE 1\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; update t_fill_100 set b = 'dummy' where a = 2;\nUPDATE 1\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select ctid, * from t_fill_75 where a &lt; 6;\n  ctid  | a |                b\n--------+---+----------------------------------\n (0,1)  | 1 | c4ca4238a0b923820dcc509a6f75849b\n (0,3)  | 3 | eccbc87e4b5ce2fe28308fd9f2a7baf3\n (0,4)  | 4 | a87ff679a2f3e71d9181a67b7542122c\n (0,5)  | 5 | e4da3b7fbbce2345d7772b0674a318d5\n (0,91) | 2 | dummy\n(5 rows)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select ctid, * from t_fill_100 where a &lt; 6;\n  ctid  | a |                b\n--------+---+----------------------------------\n (0,1)  | 1 | c4ca4238a0b923820dcc509a6f75849b\n (0,3)  | 3 | eccbc87e4b5ce2fe28308fd9f2a7baf3\n (0,4)  | 4 | a87ff679a2f3e71d9181a67b7542122c\n (0,5)  | 5 | e4da3b7fbbce2345d7772b0674a318d5\n (8,41) | 2 | dummy          &lt;-- Number 8 indicates that you are on block 8\n(5 rows)\n<\/pre>\n<p>With the following query you check out the number of hot updates that happened on a particular table.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; select relname,n_tup_hot_upd from pg_stat_user_tables where relname in ('t_fill_75','t_fill_100');\n  relname   | n_tup_hot_upd\n------------+---------------\n t_fill_75  |             1\n t_fill_100 |             0\n(2 rows)\n\n<\/pre>\n<p>Now we do a little test case to see if the PostgreSQL Btree Indexes has a default fill factor of 90%.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; create table t_fill (id bigint); -- default is 100%\nCREATE TABLE\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; create index idx_100 on t_fill (id) with (fillfactor = 100); -- set fillfactor to 100%\nCREATE INDEX\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; create index idx_90_default on t_fill (id); -- default is 90%\nCREATE INDEX\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; insert into t_fill SELECT ceil(random() * 10000000) from\n&gt; generate_series(1, 10000000) AS temp (id) ;\nINSERT 0 10000000\n<\/pre>\n<p>As expected, the index with the fillfactor of 100% is smaller.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_100\n                                 List of relations\n Schema |  Name   | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+---------+-------+----------+--------+-------------+--------+-------------\n public | idx_100 | index | postgres | t_fill | permanent   | 249 MB |\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_90_default\n                                    List of relations\n Schema |      Name      | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+----------------+-------+----------+--------+-------------+--------+-------------\n public | idx_90_default | index | postgres | t_fill | permanent   | 253 MB |\n(1 row)\n<\/pre>\n<p>What happens after the update?<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; update t_fill set id = id+1 where id%100=0;\nUPDATE 100004\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_100\n                                 List of relations\n Schema |  Name   | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+---------+-------+----------+--------+-------------+--------+-------------\n public | idx_100 | index | postgres | t_fill | permanent   | 250 MB |\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_90_default\n                                    List of relations\n Schema |      Name      | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+----------------+-------+----------+--------+-------------+--------+-------------\n public | idx_90_default | index | postgres | t_fill | permanent   | 255 MB |\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; VACUUM FULL t_fill;\nVACUUM\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_100\n                                 List of relations\n Schema |  Name   | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+---------+-------+----------+--------+-------------+--------+-------------\n public | idx_100 | index | postgres | t_fill | permanent   | 169 MB |\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_90_default\n                                    List of relations\n Schema |      Name      | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+----------------+-------+----------+--------+-------------+--------+-------------\n public | idx_90_default | index | postgres | t_fill | permanent   | 187 MB |\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; update t_fill set id = id+2 where id%50=0;\nUPDATE 99309\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_100\n                                 List of relations\n Schema |  Name   | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+---------+-------+----------+--------+-------------+--------+-------------\n public | idx_100 | index | postgres | t_fill | permanent   | 310 MB |\n(1 row)\n\n(postgres@&#x5B;local]:55001)&#x5B;fill]&gt; \\di+ idx_90_default\n                                    List of relations\n Schema |      Name      | Type  |  Owner   | Table  | Persistence |  Size  | Description\n--------+----------------+-------+----------+--------+-------------+--------+-------------\n public | idx_90_default | index | postgres | t_fill | permanent   | 187 MB |\n(1 row)\n<\/pre>\n<p>To learn more about the HOT (Heap Only Tuples) feature, take a look at the readme which you can find in the PostgreSQL source code.<\/p>\n<pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n&#x5B;postgres@ocm199 13.1]$ find . -name README.HOT\n.\/postgresql-13.1\/src\/backend\/access\/heap\/README.HOT\n\n&#x5B;postgres@ocm199 13.1]$ less .\/postgresql-13.1\/src\/backend\/access\/heap\/README.HOT\nsrc\/backend\/access\/heap\/README.HOT\n\nHeap Only Tuples (HOT)\n======================\n\nThe Heap Only Tuple (HOT) feature eliminates redundant index entries and\nallows the re-use of space taken by DELETEd or obsoleted UPDATEd tuples\nwithout performing a table-wide vacuum.  It does this by allowing\nsingle-page vacuuming, also called &quot;defragmentation&quot;.\n\nNote: there is a Glossary at the end of this document that may be helpful\nfor first-time readers.\n...\n...\n...\n<\/pre>\n<h3>Conclusion<\/h3>\n<p>In case you move from Oracle to PostgreSQL it might be worth to check out little details like the fillfactor. Especially if you have tables with a huge number of updates running on it.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>It is very interesting that Oracle and PostgreSQL are going in different directions when it comes to the fillfactor. It probably has to do with the different implementation of MVCC. I am not arguing that the one or the other is better, it is just very interesting to know that they are different. So what [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"ocean_post_layout":"","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"","ocean_second_sidebar":"","ocean_disable_margins":"enable","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"","ocean_custom_header_template":"","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"","ocean_menu_typo_font_family":"","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"default","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"","ocean_post_oembed":"","ocean_post_self_hosted_media":"","ocean_post_video_embed":"","ocean_link_format":"","ocean_link_format_target":"self","ocean_quote_format":"","ocean_quote_format_link":"post","ocean_gallery_link_images":"on","ocean_gallery_id":[],"footnotes":""},"categories":[4,6],"tags":[18,21],"class_list":["post-160","post","type-post","status-publish","format-standard","hentry","category-oracle","category-postgresql","tag-oracle","tag-postgresql","entry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>PostgreSQL Fillfactor 100%\/90% - Oracle Fillfactor 90%\/100% (aka PCTFREE) - ptdb - Platinum DB<\/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:\/\/ptdb.ch\/?p=160\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PostgreSQL Fillfactor 100%\/90% - Oracle Fillfactor 90%\/100% (aka PCTFREE) - ptdb - Platinum DB\" \/>\n<meta property=\"og:description\" content=\"It is very interesting that Oracle and PostgreSQL are going in different directions when it comes to the fillfactor. 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So what [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ptdb.ch\/?p=160\" \/>\n<meta property=\"og:site_name\" content=\"ptdb - Platinum DB\" \/>\n<meta property=\"article:published_time\" content=\"2020-11-29T08:22:38+00:00\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/ptdb.ch\/?p=160\",\"url\":\"https:\/\/ptdb.ch\/?p=160\",\"name\":\"PostgreSQL Fillfactor 100%\/90% - Oracle Fillfactor 90%\/100% (aka PCTFREE) - ptdb - Platinum DB\",\"isPartOf\":{\"@id\":\"https:\/\/ptdb.ch\/#website\"},\"datePublished\":\"2020-11-29T08:22:38+00:00\",\"author\":{\"@id\":\"https:\/\/ptdb.ch\/#\/schema\/person\/0b7baf52d23e71d85e1c95442306090b\"},\"breadcrumb\":{\"@id\":\"https:\/\/ptdb.ch\/?p=160#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/ptdb.ch\/?p=160\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/ptdb.ch\/?p=160#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/ptdb.ch\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"PostgreSQL Fillfactor 100%\/90% &#8211; Oracle Fillfactor 90%\/100% (aka PCTFREE)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/ptdb.ch\/#website\",\"url\":\"https:\/\/ptdb.ch\/\",\"name\":\"ptdb - Platinum DB\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/ptdb.ch\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/ptdb.ch\/#\/schema\/person\/0b7baf52d23e71d85e1c95442306090b\",\"name\":\"admin\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/ptdb.ch\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/1a3dffc48c5f6bae0b88a9f0b2a986d48d322673fbc2880c5abbfab96e45da8a?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/1a3dffc48c5f6bae0b88a9f0b2a986d48d322673fbc2880c5abbfab96e45da8a?s=96&d=mm&r=g\",\"caption\":\"admin\"},\"sameAs\":[\"https:\/\/ptdb.ch\"],\"url\":\"https:\/\/ptdb.ch\/?author=1\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"PostgreSQL Fillfactor 100%\/90% - Oracle Fillfactor 90%\/100% (aka PCTFREE) - ptdb - Platinum DB","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/ptdb.ch\/?p=160","og_locale":"en_US","og_type":"article","og_title":"PostgreSQL Fillfactor 100%\/90% - Oracle Fillfactor 90%\/100% (aka PCTFREE) - ptdb - Platinum DB","og_description":"It is very interesting that Oracle and PostgreSQL are going in different directions when it comes to the fillfactor. It probably has to do with the different implementation of MVCC. I am not arguing that the one or the other is better, it is just very interesting to know that they are different. 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