Rockset

JUNE 21, 2022

We’re excited to announce that Rockset’s new connector with Snowflake is now available and can increase cost efficiencies for customers building real-time analytics applications. The historical data would be stored in Snowflake and brought into Rockset for analysis using the connector.

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

Cloudera

AUGUST 13, 2021

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. By modernizing the data flow, the enterprise got better insights into the business.

Data Pipeline 108

Data Pipeline Data Lake ETL Tools Unstructured Data 108

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

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

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 AWS Relational Database 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 84

Kafka Manufacturing Data Lake SQL 84

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 Raw Data Kafka 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

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