{"id":5446,"date":"2021-05-19T21:11:21","date_gmt":"2021-05-19T20:11:21","guid":{"rendered":"https:\/\/www.theoaklandgroup.co.uk\/?p=5446"},"modified":"2024-04-17T10:03:40","modified_gmt":"2024-04-17T10:03:40","slug":"should-you-use-databricks-lakehouse-instead-of-a-data-warehouse-and-or-data-lake","status":"publish","type":"post","link":"https:\/\/weareoakland.com\/blog\/should-you-use-databricks-lakehouse-instead-of-a-data-warehouse-and-or-data-lake\/","title":{"rendered":"The Pro&#8217;s and Con&#8217;s of using Data Lakehouse"},"content":{"rendered":"<p>When using your <a class=\"Hyperlink SCXW40672974 BCX8\" href=\"https:\/\/www.theoaklandgroup.co.uk\/resources\/unlocking-your-data-future\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW40672974 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW40672974 BCX8\" data-ccp-charstyle=\"Hyperlink\">Data Platform<\/span><\/span><\/span><\/a> to improve your Business Intelligence with useful dashboards, and reports, you\u2019ll more than likely want to use a Data Warehouse. Add on your data science builds and storing your raw data cheaply, plus adding a Data Lake just for good measure, and the costs soon start adding up. Running both in tandem on a data platform can have serious costs and maintenance associated.<\/p>\n<p>So, can you have the best of both worlds with the Data Lakehouse? And what is the best Lakehouse to use?<\/p>\n<p>Before we answer those questions, we must ask, &#8220;what is a Data Warehouse, Data Lake, and a Data Lakehouse?<\/p>\n<h2>What is a Data Warehouse, Data Lake, and a Data Lakehouse<\/h2>\n<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_warehouse\"><span>Data Warehouse<\/span><\/a> is a data architecture that has been around since the 90s and is still relevant today. It is where you store your tabular data in a way that can be easily used by business intelligence applications, such as <a href=\"https:\/\/www.tableau.com\/en-gb\"><span>Tableau<\/span><\/a> or <a href=\"https:\/\/powerbi.microsoft.com\/en-us\/\"><span>Power BI<\/span><\/a>, web applications, and even other data warehouses. The three most common Data Warehouse architectures are the <a href=\"https:\/\/www.kimballgroup.com\/data-warehouse-business-intelligence-resources\/kimball-techniques\/dimensional-modeling-techniques\/\"><span>Kimball Star Schema, <\/span><\/a><a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_vault_modeling\"><span>Data Vault, and <\/span><\/a><a class=\"Hyperlink SCXW188786395 BCX8\" href=\"https:\/\/www.fivetran.com\/blog\/star-schema-vs-obt\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW188786395 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW188786395 BCX8\" data-ccp-charstyle=\"Hyperlink\">One Big Table<\/span><\/span><\/span><\/a><a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_vault_modeling\"><span><span class=\"TextRun SCXW188786395 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW188786395 BCX8\">.\u00a0<\/span><\/span><\/span><\/a><\/p>\n<p>The name is also confusingly used to identify a type of Database, such as <a href=\"https:\/\/aws.amazon.com\/redshift\/?whats-new-cards.sort-by=item.additionalFields.postDateTime&amp;whats-new-cards.sort-order=desc\"><span>AWS Redshift<\/span><\/a>, <a href=\"https:\/\/azure.microsoft.com\/en-gb\/services\/synapse-analytics\/\"><span>Azure Synapse<\/span><\/a>, and<a href=\"https:\/\/www.snowflake.com\/\"><span> Snowflake<\/span><\/a>, which specialise in storing and querying large amounts of data.<\/p>\n<p>Data Warehouses have their issues they can be more expensive than a Data Lake when processing large amounts of data, and work best only when data is of reasonable quality and in a tabular structure.<\/p>\n<div id=\"attachment_5450\" style=\"width: 363px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-5450\" class=\"size-full wp-image-5450\" src=\"https:\/\/weareoakland.com\/wp-content\/uploads\/2024\/01\/Jake-blog-1.png\" alt=\"infographic\" width=\"353\" height=\"240\" \/><p id=\"caption-attachment-5450\" class=\"wp-caption-text\">Architecture of a simple data platform using just a data warehouse<\/p><\/div>\n<p>So, along came the Data Lake to help ease these common pain points:<\/p>\n<ul>\n<li>Data Scientists needing to be able to process large amounts of raw data of dubious quality.<\/li>\n<li>Increasing requirements for storage of non-tabular data sources.<\/li>\n<li>The need for data storage that is more flexible in structure and schema.<\/li>\n<li>The need to store data that might be needed at a later date, for example for auditing, but have a low set up and maintenance cost (little or no ETL process needed compared to a Database)<\/li>\n<\/ul>\n<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_lake\"><span>Data Lake<\/span><\/a> is just a distributed file system at it&#8217;s heart, usually hosted in the cloud in <a href=\"https:\/\/aws.amazon.com\/s3\/\"><span>AWS S3<\/span><\/a> or <a href=\"https:\/\/azure.microsoft.com\/en-gb\/solutions\/data-lake\/\"><span>Azure Data Lake<\/span><\/a>, with large files split by a key, so you can save on processing costs by loading only the partitions of data you need.<\/p>\n<p>Data Lakes also generally have more flexibility in that they can store an unlimited amount of file formats and offer a common interface to its storage that allows you to use many compute engines. This is often called <a class=\"Hyperlink SCXW70856486 BCX8\" href=\"https:\/\/www.starburst.io\/blog\/true-separation-of-storage-and-compute\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW70856486 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW70856486 BCX8\" data-ccp-charstyle=\"Hyperlink\">separating storage from compute<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW70856486 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW70856486 BCX8\">, <\/span><\/span>which has become so popular that many Data Warehouses offer this too now. Data Lakes can also easily store non tabular data (images, videos and music) that Data Warehouses cannot without some pre-processing.<\/p>\n<p>However, without Delta Lake it cannot easily or efficiently do row level updates and inserts. nor connect easily to business intelligence applications in the way that a Data Warehouse or Database can do.<\/p>\n<div id=\"attachment_7303\" style=\"width: 612px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-7303\" class=\"size-full wp-image-7303\" src=\"https:\/\/weareoakland.com\/wp-content\/uploads\/2024\/01\/Data-Lakehouse-Blog-Image-2.png\" alt=\"Diagram\" width=\"602\" height=\"303\" \/><p id=\"caption-attachment-7303\" class=\"wp-caption-text\">Architecture of an example data platform using both a Data Lake and a Data Warehouse<\/p><\/div>\n<h2>What is a Data Lakehouse?<\/h2>\n<p><span class=\"TextRun SCXW211226099 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">A <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">D<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">ata <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">L<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">akehouse<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\"> is <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">a<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">n<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\"> open data management architecture that combines the flexibility, cost-efficiency, and scale of <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">D<\/span><\/span><a class=\"Hyperlink SCXW211226099 BCX8\" href=\"https:\/\/www.databricks.com\/discover\/data-lakes\/introduction\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW211226099 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-charstyle=\"Hyperlink\">ata <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-charstyle=\"Hyperlink\">L<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-charstyle=\"Hyperlink\">akes<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW211226099 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\"> with the data management and ACID transactions of <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">D<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">ata <\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">W<\/span><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">arehouses, enabling business intelligence (BI) and machine learning (ML) on all data.<\/span><\/span><span class=\"TextRun SCXW211226099 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW211226099 BCX8\" data-ccp-parastyle=\"heading 1\">\u00a0<\/span><\/span><span class=\"EOP SCXW211226099 BCX8\" data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:0,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h2>What is Databricks Lakehouse?<\/h2>\n<p>Until a few years ago, <a href=\"https:\/\/databricks.com\/\"><span>Databricks<\/span><\/a> was mainly designed as an easy way to run <a href=\"https:\/\/spark.apache.org\/\"><span><span data-contrast=\"none\">Spark<\/span><\/span><\/a><span data-contrast=\"none\">,<\/span><span data-contrast=\"auto\"> a distributed data processing library for large scale Data Engineering and Data Science. It worked mainly in tandem with a Data Lake, with similar advantages and drawbacks.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In 2019 Databricks released <\/span><a href=\"https:\/\/delta.io\/\"><span><span data-contrast=\"none\">Delta Lake<\/span><\/span><\/a><span data-contrast=\"auto\">, a file format with attributes only found previously in Databases and Data Warehouses as mentioned above. Combined with Spark to process and transform a wide variety of data, this gave birth to the Data Lakehouse.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Today, Databricks has a fully featured <\/span><a href=\"https:\/\/docs.databricks.com\/sql\/admin\/create-sql-warehouse.html\"><span><span data-contrast=\"none\">SQL Data Warehouse<\/span><\/span><\/a><span data-contrast=\"auto\">, enterprise security, data governance with <\/span><a href=\"https:\/\/www.databricks.com\/product\/unity-catalog\"><span><span data-contrast=\"none\">Unity Catalog<\/span><\/span><\/a><span data-contrast=\"auto\">, <\/span><a href=\"https:\/\/docs.databricks.com\/external-data\/index.html\"><span><span data-contrast=\"none\">many data connectors<\/span><\/span><\/a><span data-contrast=\"auto\">, as well as the ability to output data to Power BI and Tableau, so it can meet all common data use cases.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-5460 aligncenter\" src=\"https:\/\/weareoakland.com\/wp-content\/uploads\/2024\/01\/Databricks-Lakehouse.png\" alt=\"\" width=\"1086\" height=\"498\" \/><\/p>\n<p style=\"text-align: center;\">Architecture of a simple data platform using just both a Data Lake and Data Warehouse.<\/p>\n<p><span class=\"TextRun SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW10269064 BCX8\">For those looking at building a Data Mesh<\/span><span class=\"NormalTextRun SCXW10269064 BCX8\">,<\/span> <\/span><a class=\"Hyperlink SCXW10269064 BCX8\" href=\"https:\/\/docs.databricks.com\/query-federation\/index.html\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW10269064 BCX8\" data-ccp-charstyle=\"Hyperlink\">Databricks has federated query<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW10269064 BCX8\"> in <\/span><span class=\"NormalTextRun SCXW10269064 BCX8\">preview,<\/span> <span class=\"NormalTextRun SCXW10269064 BCX8\">though<\/span><span class=\"NormalTextRun SCXW10269064 BCX8\"> Delta Lake<\/span><span class=\"NormalTextRun SCXW10269064 BCX8\"> also<\/span><span class=\"NormalTextRun SCXW10269064 BCX8\"> has connectors for <\/span><\/span><a class=\"Hyperlink SCXW10269064 BCX8\" href=\"https:\/\/trino.io\/docs\/current\/connector\/delta-lake.html\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW10269064 BCX8\" data-ccp-charstyle=\"Hyperlink\">Trino<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW10269064 BCX8\">, <\/span><\/span><a class=\"Hyperlink SCXW10269064 BCX8\" href=\"https:\/\/docs.starburst.io\/latest\/connector\/starburst-delta-lake.html\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW10269064 BCX8\" data-ccp-charstyle=\"Hyperlink\">Starburst<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW10269064 BCX8\"> and <\/span><\/span><a class=\"Hyperlink SCXW10269064 BCX8\" href=\"https:\/\/docs.dremio.com\/software\/data-formats\/delta-lake\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span><span class=\"TextRun Underlined SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\"><span class=\"NormalTextRun SpellingErrorV2Themed SCXW10269064 BCX8\" data-ccp-charstyle=\"Hyperlink\">Dremio<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW10269064 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"> <span class=\"NormalTextRun SCXW10269064 BCX8\">so<\/span> <span class=\"NormalTextRun SCXW10269064 BCX8\">you can join up many <\/span><span class=\"NormalTextRun SCXW10269064 BCX8\">Data Lakes across your organisation.<\/span><\/span><\/p>\n<div id=\"attachment_7304\" style=\"width: 1389px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-7304\" class=\"size-full wp-image-7304\" src=\"https:\/\/weareoakland.com\/wp-content\/uploads\/2024\/01\/Lakehouse-Blog-Image-3.png\" alt=\"Architecture\" width=\"1379\" height=\"1401\" \/><p id=\"caption-attachment-7304\" class=\"wp-caption-text\">Architecture of many Lakehouse Data Products in a Data Mesh &#8211; the query layer and governance layer will have access to all Data Products, limited by access permissions.<\/p><\/div>\n<h2>Will I still need a Data Warehouse?<\/h2>\n<p><span data-contrast=\"auto\">Maybe, but note it may take some time for a data team used to Databases\/Data Warehouses and SQL to convert to Data Lakehouse. Here at Oakland we feel it is still easier to set up and optimise Cloud Native Warehouses like <\/span><a href=\"https:\/\/www.snowflake.com\/en\/\"><span><span data-contrast=\"none\">Snowflake<\/span><\/span><\/a><span data-contrast=\"auto\"> and <\/span><a href=\"https:\/\/cloud.google.com\/bigquery\"><span><span data-contrast=\"none\">Google Big Query<\/span><\/span><\/a><span data-contrast=\"auto\">, than Databricks, as there are fewer moving parts.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">These maintenance costs can far outweigh the benefits of the Lakehouse, generally at smaller scales and data complexity.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Also, while we\u2019ve seen first-hand that Lakehouse can be the cheaper and more performant option than a Data Warehouse, this hasn\u2019t been the case 100% of the time and you should do your own testing, as performance and cost heavily depends on the data you use and the environment you operate in.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h2>Can I build a Lakehouse somewhere other than Databricks?<\/h2>\n<p><span class=\"TextRun SCXW206255829 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW206255829 BCX8\">Yes, Delta Lake is open source<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> and<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> can be used <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">in many different data compute products <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">which are <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">listed below<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">. However<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">,<\/span> <span class=\"NormalTextRun SCXW206255829 BCX8\">Databricks <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">has built in <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">special optimisations<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> just for Databricks<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> and a <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">robust <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">u<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">ser <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">i<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">nterface to manage the Lakehouse<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">. <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">So, it is <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">likely running<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> Delta Lake will be slower and <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">could be <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">harder<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> to <\/span><span class=\"NormalTextRun SCXW206255829 BCX8\">maintain<\/span><span class=\"NormalTextRun SCXW206255829 BCX8\"> elsewhere.<\/span><\/span><span class=\"EOP SCXW206255829 BCX8\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<div id=\"attachment_7305\" style=\"width: 612px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-7305\" class=\"size-full wp-image-7305\" src=\"https:\/\/weareoakland.com\/wp-content\/uploads\/2024\/01\/Lakehouse-Blog-4.png\" alt=\"Diagram\" width=\"602\" height=\"322\" \/><p id=\"caption-attachment-7305\" class=\"wp-caption-text\">Databricks user interface for datasets showing the schema and a sample of the dataset<\/p><\/div>\n<p><span data-contrast=\"auto\">Also note that Databricks is a general compute engine rather than a database or programming interface: it can run SQL, Pandas, <\/span><a href=\"https:\/\/www.databricks.com\/blog\/2021\/11\/19\/ray-on-databricks.html\"><span><span data-contrast=\"none\">Ray<\/span><\/span><\/a><span data-contrast=\"auto\">, Spark, most of the popular data science libraries, do graph analytics, geospatial, IoT, near-real time streaming and import almost any Python, Java, R or Scala library. Databricks\u2019 main benefit to us is its extreme versatility, potentially reducing costs by not having to maintain separate business intelligence and data science data processing applications.\u00a0\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Also, Databricks is in strong position to customise <\/span><a href=\"https:\/\/www.analyticsvidhya.com\/blog\/2023\/03\/an-introduction-to-large-language-models-llms\"><span><span data-contrast=\"none\">Large Learning Models (LLMs)<\/span><\/span><\/a><span data-contrast=\"auto\"> like ChatGPT, with its general compute and strong <\/span><a href=\"https:\/\/mlflow.org\/\"><span><span data-contrast=\"none\">MLflow<\/span><\/span><\/a><span data-contrast=\"auto\"> integration, so you can pick the best open-source AI models and tune it with your organisational data in a highly efficient way using <\/span><a href=\"https:\/\/www.databricks.com\/glossary\/mlops\"><span><span data-contrast=\"none\">MLOps<\/span><\/span><\/a><span data-contrast=\"auto\">.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">However, if you\u2019re already using one of the Lakehouse alternatives listed below, it may not be worth adding Databricks to your Data Platform.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The alternatives to Databricks Lakehouse are:\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Build your own Lakehouse using open-source Delta Lake, <\/span><a href=\"https:\/\/hudi.apache.org\/\"><span><span data-contrast=\"none\">Apache Hudi<\/span><\/span><\/a><span data-contrast=\"auto\"> or <\/span><a href=\"https:\/\/iceberg.apache.org\/\"><span><span data-contrast=\"none\">Apache Iceberg.<\/span><\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li><span data-contrast=\"auto\">Iceberg <\/span><a href=\"https:\/\/www.dremio.com\/subsurface\/why-and-how-netflix-created-and-migrated-to-a-new-table-format-iceberg\/\"><span><span data-contrast=\"none\">used by Netflix<\/span><\/span><\/a><span data-contrast=\"auto\"> and <\/span><a href=\"https:\/\/iceberg.apache.org\/vendors\/\"><span><span data-contrast=\"none\">has support from a variety of major vendors<\/span><\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">Hudi is also used by major enterprises, including <\/span><a href=\"https:\/\/medium.com\/walmartglobaltech\/lakehouse-at-fortune-1-scale-480bcb10391b\"><span><span data-contrast=\"none\">Walmart<\/span><\/span><\/a><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><a href=\"https:\/\/www.starburst.io\/solutions\/data-lakehouse\/\"><span><span data-contrast=\"none\">Starburst<\/span><\/span><\/a><span data-contrast=\"auto\">, like Databricks, is a cloud neutral and cloud native compute engine with a full suite of enterprise options and data connectors. It has Delta Lake and Iceberg connectors that can be fully controlled with a SQL API.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/learn.microsoft.com\/en-us\/azure\/synapse-analytics\/spark\/apache-spark-overview\"><span><span data-contrast=\"none\">Azure Synapse<\/span><\/span><\/a><span data-contrast=\"auto\"> has the option to use its own Spark Engine, can import Java and Python libraries, and has Delta Lake Integration too. Has excellent integration with rest of Azure.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/aws.amazon.com\/blogs\/big-data\/introducing-aws-glue-3-0-with-optimized-apache-spark-3-1-runtime-for-faster-data-integration\/\"><span><span data-contrast=\"none\">AWS Glue<\/span><\/span><\/a><span data-contrast=\"auto\"> allows you to use Delta Lake in S3. Has excellent integration with rest of AWS.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559685&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><span data-contrast=\"auto\">Some may say <\/span><a href=\"https:\/\/pandas.pydata.org\/\"><span><span data-contrast=\"none\">Pandas<\/span><\/span><\/a><span data-contrast=\"auto\"> or <\/span><a href=\"https:\/\/duckdb.org\/\"><span><span data-contrast=\"none\">DuckDB<\/span><\/span><\/a><span data-contrast=\"auto\"> can be a Data Lakehouse, though from our research in May 2023 they cannot do transactions or merges on a Data Lake file (Delta Lake, Iceberg, etc.) so have been excluded from the above &#8211; they still have their own use cases though.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559685&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h2 aria-level=\"1\"><span data-contrast=\"none\">Summary<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:0,&quot;335559740&quot;:259}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"auto\">In short, like with other data products and architectures, the answer is it depends on the makeup of your data team, security, the size and structure of your data, and how the data is used among many other factors.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">If you are consuming a lot of data in your data platform, struggling to manage both a Data Lake and Data Warehouse at the same time, or trying to figure out how to use advanced analytics like Machine Learning with your data, Data Lakehouse is in our opinion a convincing proposition.\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">We also find ourselves recommending Databricks more often than the alternatives as it offers the most complete Lakehouse solution, though competitors are quickly catching up and offering a near as good as experience as Databricks, so the choice isn\u2019t as easy to make as it was in 2021 when we first wrote this article.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When using your Data Platform to improve your Business Intelligence with useful dashboards, and reports, you\u2019ll more than likely want to use a Data Warehouse. Add on your data science builds and storing your raw data cheaply, plus adding a Data Lake just for good measure, and the costs soon start adding up. Running both&#8230;<\/p>\n","protected":false},"author":15,"featured_media":3887,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[406,160],"tags":[292,293,294,295,296,297,298,299,139,126,273,300,301,302],"class_list":["post-5446","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-platform-data-engineering","category-tech-talk","tag-acid-transactions","tag-apache-spark","tag-aws-redshift","tag-aws-s3","tag-azure-data-lake","tag-azure-synapse","tag-data-lake","tag-data-vault","tag-data-warehouse","tag-databricks","tag-delta-lake","tag-kimball-star-schema","tag-snowflake","tag-sqp-analytics"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.2 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>The Pro&#039;s and Con&#039;s of using Data Lakehouse | 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