Rockset

MARCH 24, 2022

This requires a database to automatically ingest and index semi-structured data and generate an underlying schema even as data shape changes. Relational and non-relational databases each have their own unique challenges when it comes to query flexibility. What databases are you using for real-time analytics?

Non-relational Database 52

Non-relational Database Relational Database Database Data Pipeline 52

Knowledge Hut

JULY 26, 2023

Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relational databases. Key-value stores, columnar stores, graph-based databases, and wide-column stores are common classifications for NoSQL databases. Columnar Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

Rockset

JULY 6, 2022

Typically stored in SQL statements, the schema also defines all the tables in the database and their relationship to each other. Rockset is a real-time analytics platform built on top of the RocksDB key-value store. Like other NoSQL databases, Rockset is highly scalable, flexible and fast at writing data.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Rockset

FEBRUARY 2, 2022

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. These databases can serve real-time data applications, unlike the data warehouses we considered previously.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Rockset

AUGUST 4, 2021

Operational Analytics Applications such as e-commerce, gaming, and the Internet of things (IoT) commonly require real-time views of what’s happening on a site, in a game, or at a manufacturing plant. Next Steps Snowflake’s scalable relational database is cloud-native.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 40

ProjectPro

FEBRUARY 16, 2023

Data engineers are responsible for these data integration and ELT tasks, where the initial step requires extracting data from different types of databases/files, such as RDBMS, flat files, etc. SQL in Big Data SQL is not just limited to data warehousing and traditional relational database management systems (RDBMS).

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

An object-centric data model is a big deal because it offers the opportunity for a holistic approach and as a database a single source of truth for Process Mining but also for other types of analytical applications. the type material will have different attributes then the type invoice or department ).

Architecture 52

Architecture Database-centric Process BI 52