In today's modern ecosystem, the biggest challenge with data is figuring out how to leverage it to drive business insights and actions. The data warehouse plays a huge role in this journey as the crucial middleman between data storage and action.
A data warehouse is used for storing, centralizing, and querying large volumes of data. It's often used in conjunction with business intelligence and operations automations tools like LogicLoop. Data warehouses can contain data from various difference sources, by syncing data from production databases, external sources, SaaS applications and more through a process called ETL. Data warehouses are often used for analytical purposes such as for querying data to analyze vital business info, but they are also used for operational purposes such as to query data to trigger alerts and actions.
The main benefit of a data warehouse is that it is one central source of truth to help aid decisioning across your entire organization. Companies would rather query their data warehouse than their production database directly because data warehouses can generally handle more scale intensity and querying the warehouse is safer than querying your production directly as you wouldn't want intensive queries can stall your live production database.
With today's cloud technologies, the ease and cost of setting up a data warehouse has been significantly reduced. Modern day data warehouses can handle large volumes of data and are highly efficient and scalable. Let's take a look at the best data warehouses available on the market today.
Redshift is a highly efficient and scalable data warehouse hosted in the cloud by Amazon in their AWS ecosystem. It is a relational database and can be used to query structured data easily using SQL and a data analysis tool. AWS Redshift can connect to a number of data tools like LogicLoop, Looker, Mode and more. Redshift was built to prioritize easy of use, speed, and scalability with its parallel processing design. Redshift is widely adopted for data reporting and operations automation use cases. Since it was one of the first warehouses to hit the market, it has been seen as a pioneer in the movement for the past decade. However, it only recently added features to separate compute and storage. Regardless, it is by far one of the most popular data warehouses used by startups and large companies alike today.
Snowflake is another data warehouse based in the cloud and can be deployed in both the Azure and AWS ecosystems. Snowflake separates compute and storage so those two functions can scale independently, allowing customers to have more flexibility when it comes to where they are willing to pay more. They charge dynamically based on usage. You must used the SQL language in order to view and manipulate data in the Snowflake.
BigQuery is a warehouse that is serverless and lives on the Google Cloud Platform. It's very easy to set up and they even give you some space for free to start. Launched in 2011, Google BigQuery was design to read a massive volume of data in the billions for data analysis and actioning. Similar to the other data warehouses, Big Query data can be accessed using SQL but is actually a hybrid system that also has NoSQL features. BigQuery tends to be the fan favorite among machine learning engineerings and data scientists who have to deal with huge datasets as it can execute queries very quickly.
Azure Synapse Analytics is a cloud data warehouse hosted in the Azure ecosystem. If you're already operating in the Microsoft Azure ecosystem, Synapse Analytics is a no brainer as it has an easy integration with Microsoft SQL Server. However, if you're using other databases and tools, it is not as integration friendly as some of the other options. Synapse Analytics also comes with advanced security features such as row-level security and data masking.
There are many data warehouses on the market today, but the behemoths of Amazon, Google, and Microsoft definitely take the lead today in terms of speed and volume with the massive compute power and research budget these firms have. If you're a modern software company with large volumes of data, Redshift, Snowflake, Big Query and Azure are four fantastic options to consider.
Once you have chosen your database warehouse, you'll want to take full advantage of it's capabilities by setting up alerts & automations on top it to monitor and streamline your business processes. You can get started quickly here with LogicLoop, which supports all popular data warehouses detailed above. Happy querying!