{"id":679,"date":"2026-04-20T08:24:02","date_gmt":"2026-04-20T08:24:02","guid":{"rendered":"https:\/\/innohub.powerweave.com\/?p=679"},"modified":"2026-04-20T08:24:02","modified_gmt":"2026-04-20T08:24:02","slug":"why-netflix-instagram-and-twitter-pick-different-databases","status":"publish","type":"post","link":"https:\/\/innohub.powerweave.com\/?p=679","title":{"rendered":"Why Netflix, Instagram, and Twitter Pick Different Databases"},"content":{"rendered":"\n<p>Choosing a database isn&#8217;t about finding the &#8220;best&#8221; technology; it&#8217;s about matching a database&#8217;s strengths to your specific <strong>access patterns<\/strong>. In a recent architectural deep dive, the channel <em>ByteMonk<\/em> explained why three of the world\u2019s largest platforms chose fundamentally different database paths. [<a target=\"_blank\" rel=\"noreferrer noopener\" href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=23\">00:23<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"Why Netflix, Instagram, and Twitter Pick Different Databases\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/XjHZCprrEgk?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">1. Netflix: High-Write Throughput with Cassandra<\/h3>\n\n\n\n<p>Netflix handles over <strong>3 million writes per second<\/strong> as it tracks every pause, hover, and search from 260 million subscribers. [<a target=\"_blank\" rel=\"noreferrer noopener\" href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=80\">01:20<\/a>]<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>The Choice:<\/strong> <strong>Apache Cassandra<\/strong>.<\/li>\n\n\n\n<li><strong>Why:<\/strong> Cassandra is built for horizontal write scaling. It acts like a distributed hashmap, routing writes to specific nodes with minimal overhead. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=106\" target=\"_blank\" rel=\"noreferrer noopener\">01:46<\/a>]<\/li>\n\n\n\n<li><strong>The Trade-off:<\/strong> No joins or ad-hoc SQL queries. Netflix must model its data around specific queries rather than entities, often duplicating data across different tables to ensure every read is a simple key lookup. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=147\" target=\"_blank\" rel=\"noreferrer noopener\">02:27<\/a>]<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2. Instagram: Relational Complexity with PostgreSQL<\/h3>\n\n\n\n<p>Instagram\u2019s core workload is <strong>read-heavy<\/strong> and <strong>highly relational<\/strong>. Feeds require joining posts with follow relationships, and profiles need aggregated counts. [<a target=\"_blank\" rel=\"noreferrer noopener\" href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=215\">03:35<\/a>]<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>The Choice:<\/strong> <strong>PostgreSQL<\/strong>.<\/li>\n\n\n\n<li><strong>Why:<\/strong> PostgreSQL excels at joins, aggregations, and complex filtering. Instagram proved that you don&#8217;t need NoSQL just because you have a billion users; you can scale SQL using connection pooling (PG Bouncer), read replicas, and partitioning. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=307\" target=\"_blank\" rel=\"noreferrer noopener\">05:07<\/a>]<\/li>\n\n\n\n<li><strong>The Trade-off:<\/strong> Massive write volumes are harder to handle than in Cassandra. Instagram accepts the engineering complexity of sharding and indexing to keep the flexibility of relational queries. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=332\" target=\"_blank\" rel=\"noreferrer noopener\">05:32<\/a>]<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">3. Twitter: Ultra-Low Latency with Redis<\/h3>\n\n\n\n<p>Twitter\u2019s challenge is the <strong>timeline<\/strong>. When you open the app, you expect to see a merged list of tweets from thousands of accounts instantly. [<a target=\"_blank\" rel=\"noreferrer noopener\" href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=369\">06:09<\/a>]<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>The Choice:<\/strong> <strong>Redis<\/strong> (as a cache).<\/li>\n\n\n\n<li><strong>Why:<\/strong> Redis operates entirely in memory, serving precomputed timelines at <strong>300,000 requests per second<\/strong>. Twitter uses a &#8220;Fan-out on Write&#8221; approach, pushing new tweets into the Redis caches of every follower so the timeline is already assembled when the user logs in. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=421\" target=\"_blank\" rel=\"noreferrer noopener\">07:01<\/a>]<\/li>\n\n\n\n<li><strong>The Trade-off:<\/strong> Redis is not durable and can lose data on restart. Twitter uses it only as a cache, with a durable database (like Manhattan or MySQL) as the primary source of truth. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=451\" target=\"_blank\" rel=\"noreferrer noopener\">07:31<\/a>]<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">How to Choose Your Database<\/h3>\n\n\n\n<p>To make the right choice, ask yourself three questions: [<a target=\"_blank\" rel=\"noreferrer noopener\" href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=538\">08:58<\/a>]<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li><strong>What is the access pattern?<\/strong> Relational queries (Postgres), massive writes (Cassandra), or ultra-low latency reads (Redis)?<\/li>\n\n\n\n<li><strong>What are you willing to sacrifice?<\/strong> Flexibility, write scale, or data durability?<\/li>\n\n\n\n<li><strong>Do you actually need it?<\/strong> Most apps don&#8217;t need a distributed NoSQL system; a well-indexed Postgres instance can handle 95% of use cases. [<a href=\"http:\/\/www.youtube.com\/watch?v=XjHZCprrEgk&amp;t=581\" target=\"_blank\" rel=\"noreferrer noopener\">09:41<\/a>]<\/li>\n<\/ol>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Choosing a database isn&#8217;t about finding the &#8220;best&#8221; technology; it&#8217;s about matching a database&#8217;s strengths to your specific access patterns. In a recent architectural deep dive, the channel ByteMonk explained why three of the world\u2019s largest platforms chose fundamentally different database paths. [00:23] 1. Netflix: High-Write Throughput with Cassandra Netflix handles over 3 million writes [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":680,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[825,71,46,161],"tags":[1031,1025,1030,1027,49,183,1032,1026,1029,1028],"class_list":["post-679","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science","category-data-security","category-database","category-mongodb","tag-apache-cassandra","tag-database-choice","tag-instagram-tech-stack","tag-netflix-architecture","tag-postgresql","tag-redis","tag-scalability","tag-sql-vs-nosql","tag-system-design-interview","tag-twitter-timeline"],"jetpack_featured_media_url":"https:\/\/innohub.powerweave.com\/wp-content\/uploads\/2026\/04\/8.jpg","_links":{"self":[{"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/posts\/679","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=679"}],"version-history":[{"count":1,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/posts\/679\/revisions"}],"predecessor-version":[{"id":681,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/posts\/679\/revisions\/681"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=\/wp\/v2\/media\/680"}],"wp:attachment":[{"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=679"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=679"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/innohub.powerweave.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=679"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}