Best Cloud Database – In 2012, Amazon released the first cloud database DynamoDB and changed the on-premises database forever. Since then, cloud databases have experienced a meteoric rise in terms of adoption and innovation. As the entire Software development industry is moving towards cloud environment development, cloud storage will become more important in the coming days. Gartner predicts that by the end of 2022, 75% of all data storage will move to the Cloud:
Gartner Says The Future Of The Cloud Data Market By 2022, 75% of all data storage will be deployed or migrated to a cloud platform, only 5% has been considered… www.gartner.com
Best Cloud Database
Why are cloud databases popular? In terms of database technology, public cloud databases are not the same as other SQL or NoSQL databases. However, the main selling point of public cloud storage lies in database management and scalability.
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In traditional SQL databases and many NoSQL databases, application owners manage the database, including replication, distribution, storage, retrieval, and measurement. But in a cloud database, the cloud provider manages the database.
Although SQL and NoSQL databases are currently trying to replicate these features, they are not built from the ground up with these needs in mind.
During the December 2004 Christmas sales, Amazon learned the hard way that a medium-sized, robust, static RDBMS could not handle a Web-Scale application load. With a strict model of consistency, relational architecture, and phase 2 commitment, the traditional SQL database could not provide the high availability and horizontal scaling that Amazon wanted. The Amazon Engineering team developed a new NoSQL database called DynamoDB and released their results on their Dynamo page in 2007. The Amazon Dynamo page played an important role in the later development of NoSQL databases such as Cassandra, Riak.
Although DynamoDB was used as the main database for Amazon’s shopping cart application, it was only made public in 2012. Since then, DynmoDB is the most popular cloud database and one of the most popular AWS services.
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Amazon DynamoDB is one of the most widely used hyper-scale cloud databases. It is also one of the most popular AWS services.
In recent years, it has received strong competition from open source databases (for example, Cassandra, MongoDB) and other public cloud databases (Azure Cosmos DB).
As Amazon is the leading cloud provider, DynamoDB is still the most popular NoSQL database in the public cloud.
According to DB-Engines’ popular database environment, it is the second most popular public cloud database environment, just after Azure SQL Database:
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The Stack Overflow Developer Survey 2020 ranked DynamoDB as the 11th most popular database in 2020. This is a game considering that DynamoDB was the only public cloud database on the list:
Since its launch in 2012, DynamoDB has been one of the industry’s leading databases. DB-Engines shows the continuous growth of DynamoDB throughout its life:
There are few companies out there that have to deal with big data like Google. It’s no wonder that Google is leading the BigData landscape in the 21st century with many new ideas and innovations. At the beginning of this century, Google found the “One size fits all” SQL database was not good enough for the analytical load. They have created a new Database, “Dremel,” for data storage, that is, to handle large volumes of Data for analytics. Google published a paper, “Dremel: Functional Analysis of Web-Scale Datasets,” in 2010 to make their findings public.
Later, Google made their internal Dremel Database public as BigQuery Database in 2011. Since then, it is the most important and the most innovative thing in Data storage and analysis workload. Google Cloud (GCP) has a strong presence in the Data Storage space, and BigQuery plays an important role there.
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BigQuery has revolutionized data warehousing. It is the third most popular Cloud Database in terms of DB-Engines:
It is one of the best Data Storage solutions and generating a lot of hype in recent years, as shown below:
Microsoft is another big player in the database space. With Microsoft SQL Server, Microsoft dominated the database market for its mid-range Windows operating systems. When Microsoft adopted its first approach to the Cloud during the 2010s, it offered a managed database service over Microsoft SQL Server. In the following years, Microsoft’s management of SQL Server went through many changes.
Currently, Azure SQL Database is not only a managed database-as-a-service for Microsoft SQL Server, but also offers many additional features. For many businesses, especially those that already use Microsoft SQL Server, it is the cloud database of choice as they can easily upgrade and replace their Microsoft SQL Server in the cloud.
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Azure SQL Database is not as disruptive or innovative as other databases on this list. But there is a huge market for managed SQL databases in the cloud. In this area, Azure SQL database excels.
Azure SQL Database is not like the other databases on this list. But it still produces positive trends over the past decade with a major spike last year:
Microsoft is a large Tech company with a global presence. When Microsoft started the Cloud-first policy in 2010, they wanted to develop their Planet-Scale NoSQL database to emphasize greater flexibility and developer friendliness. Finally, after seven years of intensive research and development, they released their multi-model, multi-consistency, Database Azure Cosmos DB distributed globally in 2017. In many ways, Azure Cosmos DB introduces many novel features to Database Technology. Although it is not the first multimodel database, it is the main multimodel database. It also provides additional features useful to the developer.
Today, Azure Cosmos DB is one of the fastest growing databases on the market. These days, the search for a “Master Database,” that is, “one database to rule them all,” is a hot topic. Among all the possible candidates for “Master Database”, Azure Cosmos DB is the most suitable candidate at the moment.
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Azure Cosmos DB is the smallest database in this range and has only been on the market for the last four years. However, it has received the highest adoption in the industry and is ranked 4th in popularity of cloud data:
As a leading cloud provider and pioneer, Amazon wanted to move quickly. Amazon, famously or not, has taken many open data stores and built their AWS service on top of them. When Google shook up the Data Warehouse scene in 2011 with the Big Question, Amazon took the popular and innovative SQL database PostgreSQL and built its own database solution on top of it. In 2013, they released Amazon Redshift as a cloud data storage solution.
Amazon Redshift is one of the leading data storage solutions thanks to AWS management in the public cloud environment. On the flip side, Amazon Redshift is not as fast as its competitors (eg, BigQuery, Snowflake) because of its strong dependency on PostgreSQL.
In terms of popularity, Amazon Redshift is behind the other cloud databases on this list, as shown below:
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Amazon Redshift is not the best data warehousing solution on the market and is behind BigQuery and Snowflake. In recent years, its traction has softened, as shown by DB-Engine’s leading:
Google BigQuery has revolutionized the Data Warehouse landscape and is the most emerging data warehousing solution. Amazon Redshift is another popular data storage solution built on PostgreSQL server.
Although relatively new, Azure Cosmos DB is a very promising database and a leading contender for data storage.
Many other public cloud databases failed to make this short list. Among them, Google Spanner and Amazon Aurora are very promising in the landscape of Distributed SQL databases.
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If you are already in a public cloud or planning to move to a public cloud, you should reconsider the public cloud database. Public cloud storage is here to stay and will provide managed storage for a variety of purposes in the future.
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Lead Solution Architect | Certified AWS/AZURE/GCP Architect | Full stack | Cloud | Big Data | Follow me on Twitter: https://twitter.com/KamaruzzMdChoosing the right database for your application is not easy. The choice depends largely on your use case – transaction processing, analytical processing, in-memory database, etc. – but it depends on other factors. This post covers the different database options available within Google in both relational (SQL) and non-relational (NoSQL) environments and explains which use cases are best suited for each database option.
Choosing the right database for your application is not easy. The choice depends largely on your use case – transaction processing, analytical processing, in-memory database, etc. – but it depends on other factors. This post covers the different database options available within Google in both relational (SQL) and non-relational (NoSQL) environments and explains which use cases are best suited for each database option.
In databases relational information is stored in tables, rows and columns, usually
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