Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. The software was subsequently open sourced in 2016. Flink, Kafka and MySQL.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Rockset

MARCH 15, 2021

For example, instead of denormalizing the data, you could use a query engine that supports joins. This will avoid unnecessary processing during data ingestion and reduce the storage bloat due to redundant data. The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e.,

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Rockset

JULY 6, 2022

It's not true and is just one of many outdated data myths that modern offerings such as Rockset are busting. I invite you to learn more about how Rockset’s architecture offers the best of traditional and modern — SQL and NoSQL — schemaless data ingestion with automatic schematization.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Knowledge Hut

JUNE 26, 2023

A complete end-to-end stream processing pipeline is shown here using an architectural diagram. The pipeline in this reference design collects data from two different sources, then conducts a join operation on related records from each stream, then enriches the output, and finally produces an average.

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. HBase architecture has three main components: HMaster, Region server, and Zookeeper.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Rockset

APRIL 15, 2022

We also combined the underlying RocksDB storage engine with our Aggregator-Tailer-Leaf (ALT) architecture so that our indexes are instantly, fully mutable. That ensures all data, even freshly-ingested out-of-order data, is available for accurate, ultra-fast (sub-second) queries.

Analytics Application 52

Analytics Application Data Warehouse Kafka Raw Data 52

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Spark has a Streaming tool that can process real-time streaming data.

Big Data 52

Big Data Coding Project Hadoop 52

Cloudera

MAY 30, 2024

By leveraging the flexibility of a data lake and the structured querying capabilities of a data warehouse, an open data lakehouse accommodates raw and processed data of various types, formats, and velocities.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines? Faster data ingestion: streaming ingestion pipelines.

Kafka 87

Kafka Manufacturing Data Lake SQL 87