Cloudera

AUGUST 31, 2021

Consideration of both data & metadata in the migration. Provides flexibility for customers to choose either Hive or Impala for SQL engine. Tight integration with SDX (Shared Data Experience). Easy UI based migration with native integrations. Validation of results for consistency checks.

Data Warehouse 86

Data Warehouse Database-centric Metadata Cloud 86

Rockset

APRIL 29, 2019

There is limited support for SQL analytics with some of these options. Developers often have a need to serve fast analytical queries over data in Amazon DynamoDB. However, as an operational database optimized for transaction processing, DynamoDB is not well-suited to delivering real-time analytics.

NoSQL 52

NoSQL PostgreSQL AWS SQL 52

ProjectPro

APRIL 1, 2016

NetworkAsia.net Hadoop is emerging as the framework of choice while dealing with big data. It can no longer be classified as a specialized skill, rather it has to become the enterprise data hub of choice and relational database to deliver on its promise of being the go to technology for Big Data Analytics.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

ProjectPro

JANUARY 19, 2022

Below, we mention a few popular databases and the different softwares used for them.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

DareData

JANUARY 30, 2023

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. DigDag: An open-source orchestrator for data engineering workflows.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Structured data is modeled to be easily searchable and occupy minimal storage space.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Big Data analytics processes and tools. Data ingestion.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

SEPTEMBER 21, 2023

In this edition of “The Good and The Bad” series, we’ll dig deep into Elasticsearch — breaking down its functionalities, advantages, and limitations to help you decide if it’s the right tool for your data-driven aspirations. Each document is a collection of fields, the basic data units to be searched. What is Elasticsearch?

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

JULY 29, 2022

On top of HDFS, the Hadoop ecosystem provides HBase , a NoSQL database designed to host large tables, with billions of rows and millions of columns. Apache Pig , Apache Hive , Apache Drill , and Apache Phoenix simplify Big Data exploration and analysis allowing for using SQL and SQL-like query languages, familiar to most data analysts.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Rockset

SEPTEMBER 3, 2020

PostgreSQL is an open-source relational database that has been around for almost three decades. This capability allows PostgreSQL to be used as a document database as well. Unlike MongoDB, PostgreSQL also allows you to store data in a more traditional row and column arrangement. What Is PostgreSQL?

MongoDB 40

MongoDB PostgreSQL SQL Database 40

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

Netflix Tech

DECEMBER 14, 2018

data access semantics that guarantee repeatable data read behavior for client applications. System Requirements Support for Structured Data The growth of NoSQL databases has broadly been accompanied with the trend of data “schemalessness” (e.g.,

Media 95

Media Database Metadata Data Schemas 95

AltexSoft

MAY 12, 2023

A fixed schema means the structure and organization of the data are predetermined and consistent. It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. Scalability. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59