Towards Data Science
JANUARY 16, 2024
Image by the author 2004 to 2010 — The elephant enters the room New wave of applications emerged — Social Media, Software observability, etc. Result: Hadoop & NoSQL frameworks emerged. New data formats emerged — JSON, Avro, Parquet, XML etc. Data lakes were introduced to store the new data formats.
ProjectPro
APRIL 17, 2015
This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. billion in 2010 to $17 billion in 2015 with estimates that the Big Data Analytics services market is growing 6 times faster than the entire IT sector. during 2014 - 2020.
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Knowledge Hut
DECEMBER 25, 2023
Databases are divided into two categories, which are NoSQL(MongoDB) and SQL(PostgreSQL, MySQL, Oracle) databases. It all started with the release of AngularJS in 2010. So, we need to choose one backend framework from Java (Spring Framework), JavaScript (NodeJS), etc, and then also learn databases.
Knowledge Hut
NOVEMBER 7, 2023
Azure was first introduced in 2010, and it has shown to be a reliable solution for businesses trying to move digitally. SQL, NoSQL, and Linux knowledge are required for database programming. The extensive list of offered services is sufficient to meet the demands of any firm in any industry.
Knowledge Hut
APRIL 26, 2024
In the age of big data processing, how to store these terabytes of data surfed over the internet was the key concern of companies until 2010. Another main aspect of this position is database design (RDBMS, NoSQL, and NewSQL), data warehousing, and setting up a data lake.
AltexSoft
SEPTEMBER 21, 2023
First publicly introduced in 2010, Elasticsearch is an advanced, open-source search and analytics engine that also functions as a NoSQL database. What is Elasticsearch? It is developed in Java and built upon the highly reputable Apache Lucene library. The engine’s core strength lies in its high-speed, near real-time searches.
ProjectPro
AUGUST 31, 2018
Azure and AWS both provide database services, regardless of whether you need a relational database or a NoSQL offering. AWS works perfectly with NoSQL and relational databases providing a mature cloud environment for big data. Azure also supports both NoSQL and relational databases and Big Data through Azure HDInsight and Azure table.
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