Rockset

FEBRUARY 18, 2021

times faster than Druid in the latest performance blog post. Real-time analytics is all about deriving insights and taking actions as soon as data is produced. When broken down into its core requirements, real-time analytics means two things: access to fresh data and fast responses to queries. Learn how Rockset is 1.67

Analytics Application 52

Analytics Application SQL Database Structured Data 52

Rockset

MARCH 10, 2022

This is the first post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them!

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Knowledge Hut

JUNE 30, 2023

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. Data engineers are experts who specialize in the design and execution of data systems and infrastructure. Who are Data Engineers?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Rockset

JULY 6, 2022

This is the fifth post in a series by Rockset's CTO and Co-founder Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! NoSQL Comes to the Rescue.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Striim

NOVEMBER 8, 2023

A data mesh is technology-agnostic and underpins four main principles described in-depth in this blog post by Zhamak Dehghani. The four data mesh principles aim to solve major difficulties that have plagued data and analytics applications for a long time.

Architecture 52

Architecture Generalist Government Datasets 52

Knowledge Hut

JULY 26, 2023

Database applications also help in data-driven decision-making by providing data analysis and reporting tools. In this blog, we will deep dive into database system applications in DBMS, and their components and look at a list of database applications. What are Database Applications? Spatial Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

Cloudera

FEBRUARY 9, 2021

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Design Detail.

Data Warehouse 67

Data Warehouse Cloud Kafka Cloud Storage 67

Rockset

MARCH 19, 2020

Intro In recent years, Kafka has become synonymous with “streaming,” and with features like Kafka Streams, KSQL, joins, and integrations into sinks like Elasticsearch and Druid, there are more ways than ever to build a real-time analytics application around streaming data in Kafka. No more stale, pre-joined data!

Kafka 40

Kafka Database Process SQL 40

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It has been designed and developed as an open community standard to ensure compatibility across languages and implementations.

Metadata 87

Metadata Data Warehouse BI AWS 87

ProjectPro

FEBRUARY 11, 2021

Having that designation means you can build end-to-end machine learning solutions , which is a highly marketable skill set considering the fact that it has been the fastest-growing job title in the world since 2019. But what does it actually take to achieve the designation of a machine learning engineer?

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 40

ProjectPro

FEBRUARY 16, 2023

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. Did you know SQL is the top skill listed in 73.4% of data engineer job postings on Indeed?

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Workfall

JUNE 27, 2023

In this blog, we’ll explore how to harness the power of Kafka to streamline event streaming within a microservices architecture and unlock its full potential for building scalable and responsive systems. Log Aggregation and Analytics: Kafka’s durable and fault-tolerant design makes it an excellent choice for log aggregation.

Kafka 75

Kafka Architecture AWS Transportation 75

Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Flexible schema : JSON allows for flexible schema design, which is useful for handling data that may change over time.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 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 post Object-centric Process Mining on Data Mesh Architectures appeared first on Data Science Blog (English only).

Architecture 52

Architecture Database-centric Process BI 52

Rockset

MARCH 15, 2021

The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e., and your solution will only be able to provide valuable real-time analytics if you are able to meet them. Indexing Efficiency Indexing data is another crucial requirement for real-time analytics applications.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Cloudera

SEPTEMBER 15, 2022

It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API. Please refer to our earlier Cloudera blog for more details about Ozone’s performance benefits and atomicity guarantees. Bucket types.

Systems 86

Systems Hadoop Metadata Telecommunication 86

Rockset

JANUARY 23, 2024

When building applications on change data capture (CDC) data using Elasticsearch, you’ll want to architect the system to handle frequent updates or modifications to the existing documents in an index. In this blog, we’ll walk through the different options available for updates including full updates, partial updates and scripted updates.

Metadata 52

Metadata Coding Analytics Application Python 52

phData: Data Engineering

MAY 11, 2023

In the latest previews of Matillion Designer, we can see that source control is seamlessly incorporated. The next-generation Matillion Designer SaaS offering balances accessibility with a very minor learning curve on Git. The hallmarks of this method are modular design and effective organization skills. Errors always arise.

Coding 52

Coding Software Engineer Software Engineering Government 52

Rockset

MAY 3, 2023

In this blog, we’ll walk through the benchmark framework, configuration and results. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams. Rockset achieved up to 4x higher throughput and 2.5x

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

AltexSoft

OCTOBER 21, 2022

After trying all options existing on the market — from messaging systems to ETL tools — in-house data engineers decided to design a totally new solution for metrics monitoring and user activity tracking which would handle billions of messages a day. Kafka is designed to handle numerous clients from both sides. Kafka vs ETL.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Cloudera

MARCH 6, 2018

This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications. The post Altus SDX: Shared services for cloud-based analytics appeared first on Cloudera Blog. Further, much of the value of cloud is for elastic workloads.

Cloud 40

Cloud Metadata Big Data AWS 40

Cloudera

NOVEMBER 8, 2022

It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises. These could be traditional analytics applications like Spark, Impala, or Hive, or custom applications that access a cloud object store natively. Conclusion.

Metadata 80

Metadata Algorithm Hadoop Cloud 80

Cloudera

APRIL 2, 2019

Intel Optane DC persistent memory was designed with ease of adoption in mind and therefore can be configured in two different operating modes : 1. Apache HBase® is one of many analytics applications that benefit from the capabilities of Intel Optane DC persistent memory. memory mode, and 2. app direct mode.

NoSQL 46

NoSQL Google Cloud Hadoop Machine Learning 46

Cloudera

NOVEMBER 9, 2018

Since most connected devices are not designed with security in mind and due to the fact that there is a lack of comprehensive IoT security standards today, the surge of connected devices means that there are more entry points for hackers. Drive real-time processing and analytics to IoT data – both in motion and at rest.

Banking 56

Banking Machine Learning Government Media 56

ProjectPro

SEPTEMBER 6, 2021

AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. Table of Contents AWS vs. GCP - The Cloud Battle AWS vs. Popular instances where GCP is used widely are machine learning analytics, application modernization, security, and business collaboration. Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

MAY 23, 2015

.”- said Arun Prasath, a Principal Engineer at WalmartLabs Social Genome Social Genome is a big data analytics solution developed by WalmartLabs that analyses millions and billions of Facebook messages, tweets, YouTube videos, blog postings and more. How Walmart is fighting the battle against big data skills crisis?

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. No reliability exists.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

OCTOBER 12, 2020

We believe Eventador will accelerate innovation in our Cloudera DataFlow streaming platform and deliver more business value to our customers in their real-time analytics applications. Our primary design principles are self-service, simplicity and hybrid. Stay tuned for more product updates coming soon!

Cloud 130

Cloud Process Scala Kafka 130

Rockset

APRIL 15, 2022

This is the second post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! That is called at-least-once semantics. This has some benefits.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

ProjectPro

MAY 31, 2021

This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. This project will teach you how to design and implement an event-based data integration pipeline on the Google Cloud Platform by processing data using DataFlow.

Big Data 52

Big Data Coding Project Hadoop 52

phData: Data Engineering

JULY 18, 2023

Central Source of Truth for Analytics A Cloud Data Warehouse (CDW) is a type of database that provides analytical data processing and storage capabilities within a cloud-based infrastructure. Modern Data Stacks embrace governance as a core design principle. Modern data businesses need modern data governance.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52