Data warehousing is a technology which focuses on storing and retrieving data from different sources. It enables companies to avoid manual data manipulations and the use of multiple tools, meaning you can streamline your operations for the benefit of your business.
There are two types of data warehousing solutions that businesses can invest in: a cloud-based data warehouse or an on-premises solution, and both definitely have their merits. Cloud data warehouses (CDW), however, are growing in popularity as it is the cloud provider who is responsible for the infrastructure and security, which results in significantly lower costs for the end user.
Cloud data warehouses also offer fantastic scalability opportunities to meet your business needs along with maximised uptime (almost 100%), great security, and high performance – all without the hardware costs! So, which are the top cloud data warehouse solutions for 2021, you ask? Let’s take a look…
1. Amazon Redshift from Amazon Web Services (AWS)
Amazon Redshift is a data warehouse designed for interactive analytics on large data sets. It uses the Hadoop framework and has an open source version called Apache Spark.
As a data PaaS offering, it provides storage capacity, processing power, and computational horsepower for analytics workloads and can be used by individuals or organizations for operational tasks like batch processing, data warehousing, data modeling, predictive analytics, and analyzing historical events.
Organizations using Amazon Redshift can analyze terabytes of raw data from their own databases or from external sources such as Hadoop environments of other companies. It offers a variety of ways to access the database, including direct command line access via SQLite and a standalone SQL-on-Hadoop connector which allows for direct access to datasets stored in the cloud.
Redshift is a part of AWS & offers fast query performance even for large datasets. It also provides the familiar SQL-based tools that many people are familiar with. In addition to this, it also has multiple cluster management options that suit different skill levels.
2. Google BigQuery from Google Cloud
Google BigQuery is a virtual warehouse which stores data in a cloud-based environment. It is a data processing engine that allows companies to use SQL queries to run their operations. It also provides analytics and visualization tools for businesses.
Google BigQuery has been offered as a service for over seven years, but has recently been put in the spotlight because of enterprises wanting to increase their business intelligence capabilities.
There are many companies that have used Google BigQuery as it is cheaper and easy to use compared to other popular data warehouse solutions, such as Oracle and Microsoft SQL Server. It also allows businesses to process their big data in order to get insights on new trends or for predictive purposes.
3. IBM Db2 Warehouse from IBM
IBM Db2 Warehouse is a full-featured, open-source database management system that provides data warehousing and analytical services.It was designed to provide both scalability and performance, and it’s easy to manage and use. It also provides analytics that can help companies to easily find insights in their data.
IBM Db2 Warehouse is an ideal solution for companies who are looking for a cost-effective way to store huge amounts of structured and unstructured data. With the use of the IBM Db2 Warehouse, companies can now store large amounts of raw data which can be used for different purposes like analyzing trends or monetizing their products.
4. Azure Synapse from Microsoft
Azure Synapse is a highly available, scalable, and cost-effective data analysis platform. It enables cloud computing users to analyze data from any number of sources in a highly interactive way.
A Synapse server consists of one or more Azure SQL Database instances that all have a copy of the same data model, but they are not necessarily co-located. The only requirement for the database instance to be a part of a Synapse server is that it hosts an RDS instance with an associated partitioned view on the table(s) in the database to which it belongs.
There are two types of tables in Azure SQL Database: standard tables and partitioned views.
Partitioned views are a type of database object in Azure SQL that have restrictions on what can be inserted into them. They are an ideal choice for scenarios where you want to implement a view of data or restrict access to certain columns of data.
There are two types of standard tables: table and index-organized tables. Standard tables can be used as a source of data that provides a read-only view of the data and doesn’t require any special configuration in order to use them.
5. Oracle Autonomous Data Warehouse from Oracle
Oracle Autonomous Data Warehouse (ADW) is a cloud-based data warehouse solution that provides advanced, self-service capabilities to users and administrators alike. This process has been automated and allows real time ingestion of data from diverse sources and storage in a highly available and scalable manner.
It is a flexible tool designed to meet the needs of a range of use cases including the efficient and cost-effective use of public cloud computing, scaling up enterprise-wide operations, querying huge datasets with low latency, and delivering high throughput analytics on large volumes of unstructured data.
It has a strong offering for users with diverse requirements such as time-series analysis, fast query performance, flexible content management, easy integration with third-party applications, and more.
Although it is hard to predict the future of data warehousing, there is a clear trend that data management in the future will move towards a more cloud-based architecture. These solutions are becoming increasingly popular among businesses because they offer ease of operations, scalability, and cost-efficiency.
The best cloud data warehouse solution for you will depend on your business needs – what type of operations are you using the solution for? How many employees do you have? What’s your budget?
If you are looking for a team of database experts who can help you find the right cloud-based solution for your business, get in touch with the team at Everconnect.
Been using Azure Synapse for several months, since we started implementing remote work, it suits our needs best.
I would choose a cloud-based data warehouse over and over, it’s much more flexible compared to an on-site one. If you take in account the vulnerability all businesses experience these days you would at least consider testing it.
You could also add SAP Data to the list. It’s scalable, easy to use and more than decently priced.
The choice should be made taking in account the knowledge base of your IT team, your budget, latency recs etc. You don’t just pick the one you like best, or the one your competitor uses.
Let’s not forget that Google’s three-year TCO is about 30% more affordable than other cloud data warehouse options. Add to this the ability to integrate with Google’s machine learning tools gives you the upper hand if you plan to explore the AI world in the near future.
Went with Snowflake in the end for its per second price rate thus giving me the option to only pay for what I use #bestonesofar
We’ve been successfully using Amazon Redshift with zero issues so far. Our data warehouse works great.
If you don’t know what you’re doing, chances are Amazon Redshift will fail you. You need a properly architected DWH otherwise you are just wasting your time and money.