AltexSoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. What is Kafka?

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

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 broad adoption of Apache Kafka has helped make these event streams more accessible.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Cloudera

NOVEMBER 2, 2020

Ingest 100s of TB of network event data per day . The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. The capabilities that more and more customers are asking for are: Analytics on live data AND recent data AND historical data. 200,000 queries per day.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

Rockset

MAY 3, 2023

To find out, we decided to test the streaming ingestion performance of Rockset’s next generation cloud architecture and compare it to open-source search engine Elasticsearch , a popular sink for Apache Kafka. Streaming data is on the rise with over 80% of Fortune 100 companies using Apache Kafka. Why measure streaming data ingestion?

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

AltexSoft

JULY 18, 2023

Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications. Netflix leverages Spark Streaming and Kafka for near real-time movie recommendations. The details page shows the event timeline.

Big Data 52

Big Data Data Process Process Hadoop 52

AltexSoft

SEPTEMBER 23, 2021

A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. Data access layer unites all the access points connected to the data hub (transactional application, BI systems, machine learning training software, etc).

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Rockset

FEBRUARY 25, 2021

However, Elasticsearch has several limitations that make it less suitable when it comes to running more complex analytical queries. Rockset, on the other hand, provides full-featured SQL and an API endpoint interface that allows developers to quickly join across data sources like DynamoDB and Kafka.

SQL 40

SQL Data Pipeline Kafka Database 40

Cloudera

JUNE 16, 2022

In 2015, Cloudera became one of the first vendors to provide enterprise support for Apache Kafka, which marked the genesis of the Cloudera Stream Processing (CSP) offering. Today, CSP is powered by Apache Flink and Kafka and provides a complete, enterprise-grade stream management and stateful processing solution. Who is affected?

Kafka 84

Kafka Manufacturing Data Lake SQL 84

Rockset

DECEMBER 9, 2021

Out-of-order event streams. The batch stack is not built to handle this peculiarity of event streams. Real-time data streams typically power analytical or data applications whereas batch systems were built to power static dashboards. The best event streaming solutions are cloud-based, easy to manage, and cost-effective.

Transportation 52

Transportation BI SQL Data Warehouse 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. Access Solution to Data Warehouse Design for an E-com Site 4.

Big Data 52

Big Data Coding Project Hadoop 52

Rockset

APRIL 15, 2022

So why are their analytics still crawling through in batches instead of real time? It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. In other words, events that are close in time are written to adjacent disk clusters or partitions.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52