Skip to main content

Building a Data Lake on Amazon Simple Storage Service

Amazon Simple Storage Service (S3) is a cloud-based data storage service that stores data in its native format. Data durability of S3 is always at a high of 99.999999999 (11 9s), and the data regardless of the volume is stored in a fully secured and safe ecosystem. In Amazon S3, data files that contain metadata and objects are stored in buckets for uploading. For metadata and files, the object is to be uploaded to S3. After this step, permissions can be granted on the metadata or related objects stored in the buckets.

Many competencies can be used when an S3 data lake is built on Amazon S3. These include media data processing applications, Artificial Intelligence (AI), Machine Learning (ML), big data analytics, and high-performance computing (HPC). When all these are used in conjunction, businesses get access to critical data, business intelligence, and analytics from S3 data lake and unstructured data sets.


There are several benefits of the S3 data lake.

The first is different computing and storage silos that were not there in traditional databases. Hence, the costs of each facility in relation to data processing, storage, and infrastructure maintenance can now be accurately calculated. Further, in S3 data lake, all types of data in native format can be stored including unstructured, semi-structured, and structured data, all at very affordable costs.

Again, users on S3 data lake can process, query, and implement data on both serverless and non-cluster Amazon Web Service platforms like Amazon Athena, Amazon Rekognition, Amazon Redshift Spectrum, and AWS Glue. Most importantly, payment is in proportion to the storage and computing facilities used without any flat fees.   

Comments

Popular posts from this blog

The Change Data Capture (CDC) Feature in Microsoft SQL Server

  Several issues are faced by organizations today in the areas of data security and safety and ramping up systems for preservation of historical data. Leading database platforms took steps in this regard by launching data audits, timestamps, complex queries, and triggers, one of them being Microsoft. It led the innovation when in 2005, it introduced the SQL Server CDC   with the “after date”, “after delete”, and “after insert” features. SQL Server CDC   captures and records all activities like insert, update, or delete that are applied to a SQL Server table. Changes made are available in a user-friendly relational format and metadata and information that are required for posting changes to the target databases are captured in modified rows. These are stored in change tables with the same structure as the columns in the tracked source tables. SQL Server CDC   also tracks and records changes in the mirrored tables with column structures that are the same as the source ...

The Evolution of Technology of Oracle Change Data Capture

Oracle change data capture ( CDC) was first launched with the 9i version as an in-built tool of the Oracle database. It was a tool that recorded and monitored all changes made in the user tables in a database. These changes were then stored in change tables and used in ETL applications for later processing and transferring to other data warehouses and databases. The release version of Oracle change data capture   had triggers placed in the source database. However, database administrators found this technology very invasive and did not favor it. Ultimately, Oracle changed the Oracle change data capture   technology and released it with the 10g version after naming it Oracle Streams.  The working of this release was different. Oracle change data capture   used the redo logs of the source database along with a replication tool of Oracle Streams. This technology turned out to be very successful and a highly optimized method to identify and move change data to a target ...

The Working of Microsoft SQL Server CDC

  Modern-day businesses have to preserve historical data and take measures to prevent data breaches. In this regard, Microsoft took the lead in 2005 when it launched the SQL Server CDC. The 2005 version of SQL Server CDC   had certain flaws which were ironed out in an updated release in 2008. Some of the functionalities included tracking and capturing all changes that take place in the SQL Server database tables without taking the help of additional programs and applications. Till 2016, SQL Server CDC   was offered by Microsoft in its high-end Enterprise editions but later was available in the Standard version too. SQL Server CDC   captures and records all activities like Insert, Update, and Delete applied to a SQL Server. Column information and metadata required for posting changes to the target database are recorded in modified rows that are then stored in change tables representing the architecture of the columns in the tracked source tables. SQL Server CDC ...