Rockset

JULY 6, 2022

Traditional databases, with their wholly-inflexible structures, are brittle. So are schemaless NoSQL databases, which capably ingest firehoses of data but are poor at extracting complex insights from that data. And the same risk of data errors and data downtime also exists. NoSQL Comes to the Rescue.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Rockset

JULY 28, 2022

MongoDB has grown from a basic JSON key-value store to one of the most popular NoSQL database solutions in use today. This can be used to create data lakes, populate data warehouses or for specific use cases like offloading analytics and text search. Documents in MongoDB can also have complex structures.

MongoDB 52

MongoDB Kafka NoSQL Data Lake 52

Knowledge Hut

APRIL 25, 2023

Strong programming skills: Data engineers should have a good grasp of programming languages like Python, Java, or Scala, which are commonly used in data engineering. Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Silectis

JANUARY 3, 2021

Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling. Data Integration Combining data from various, disparate sources into one unified view. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59