Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Uber Engineering

AUGUST 3, 2018

From driver and rider locations and destinations, to restaurant orders and payment transactions, every interaction on Uber’s transportation platform is driven by data.

Big Data 110

Big Data Transportation Engineering Storage 110

The Morning Paper

DECEMBER 13, 2020

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. ACM Computing Surveys, Dec. 2020, Article No.

Big Data 83

Big Data Open Source Processing Analytics 83

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. VLDB’19. For the larger more production-like query analysed in §4.2.1,

Big Data 57

Big Data Analytics Latency Azure 57

DZone

JUNE 3, 2024

This is especially the case when it comes to taking advantage of vast amounts of data stored in cloud platforms like Amazon S3 - Simple Storage Service, which has become a central repository of data types ranging from the content of web applications to big data analytics.

Big Data 271

Big Data AWS Analytics Storage 271

DZone

AUGUST 23, 2023

In the era of big data, efficient data management and query performance are critical for organizations that want to get the best operational performance from their data investments.

Big Data 130

Big Data Analytics Innovation Efficiency 130

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. Driving down the cost of Big-Data analytics. Comments ().

Big Data 108

Big Data Analytics AWS Cloud 108

DZone

JUNE 13, 2023

The reason is straightforward, today, applications generate enormous amounts of data. As we embrace new technologies like cloud computing, big data analysis, and the Internet of Things (IoT), there is a noticeable spike in the amount of data generated from different applications.

Scalability 246

Scalability IoT Big Data Internet 246

DZone

FEBRUARY 1, 2023

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2. For instance, Data Lake Storage Gen2 offers scale, file-level security, and file system semantics.

Azure 246

Azure Storage Big Data Analytics 246

DZone

MAY 25, 2024

As NetEase expands its business horizons, the logs and time series data it receives explode, and problems like surging storage costs and declining stability come. As NetEase's pick among all big data components for platform upgrades, Apache Doris fits into both scenarios and brings much faster query performance.

Best Practices 130

Best Practices Big Data Games Analytics 130

DZone

JULY 17, 2023

Apache Spark is a leading platform in the field of big data processing, known for its speed, versatility, and ease of use. Understanding Apache Spark Apache Spark is a unified computing engine designed for large-scale data processing. However, getting the most out of Spark often involves fine-tuning and optimization.

Big Data 130

Big Data Performance Open Source Tuning 130

DZone

FEBRUARY 6, 2024

If the data sources are not available then customized plugins can be developed to integrate these data sources. Grafana is used widely these days to monitor and visualize the metrics for 100s or 1000s of servers, Kubernetes Platforms, Virtual Machines, Big Data Platforms, etc.

Big Data 164

Big Data Open Source Virtualization Metrics 164

The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics.

Data Engineering 172

Data Engineering Engineering Big Data Software Engineering 172

The Netflix TechBlog

JULY 15, 2021

I was later hired into my first purely data gig where I was able to deepen my knowledge of big data. After that, I joined MySpace back at its peak as a data engineer and got my first taste of data warehousing at internet-scale. In the data engineering space, very little of the same technology remains.

Data Engineering 188

Data Engineering Engineering Entertainment Big Data 188

DZone

JANUARY 31, 2023

Big data is at the center of all business decisions these days. It refers to large volumes of data generated through different sources, and this data then provides the foundation for business decisions. There are different ways through which we can process data.

Processing 237

Processing Big Data Systems 237

The Netflix TechBlog

JANUARY 13, 2022

This blog will explore these two systems and how they perform auto-diagnosis and remediation across our Big Data Platform and Real-time infrastructure. The streaming platform recently added Data Mesh , and we need to expand Streaming Pensive to cover that.

Big Data 238

Big Data Infrastructure Metrics Games 238

Dynatrace

JUNE 26, 2023

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 183

Software Software Analytics Big Data 183

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

DZone

DECEMBER 27, 2023

The need to optimize offline data pipeline optimization has become a necessity with the growing complexity and scale of modern data pipelines. In this kickoff post, we delve into the intricacies of Apache Airflow and AWS EMR, a managed cluster platform for big data processing.

Best Practices 133

Best Practices Data Engineering Big Data Games 133

High Scalability

SEPTEMBER 14, 2020

This is a guest post by Limor Maayan-Wainstein , a senior technical writer with 10 years of experience writing about cybersecurity, big data, cloud computing, web development, and more. High performance computing (HPC) enables you to solve complex problems which cannot be solved by regular computing.

Cloud 261

Cloud Big Data Virtualization Efficiency 261

DZone

JUNE 6, 2023

This can include the use of cloud computing, artificial intelligence, big data analytics, the Internet of Things (IoT), and other digital tools. The digital transformation of businesses involves the adoption of digital technologies to change the way companies operate and deliver value to their customers.

Artificial Intelligence 130

Artificial Intelligence Systems IoT Testing 130

Scalegrid

MAY 13, 2020

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Query Optimization.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

DZone

JULY 22, 2022

Honestly, these two terms have recently been doing rounds in the big data world. These technologies specialize in transmitting large amounts of data across different trading partners and companies.

Big Data 188

Big Data Technology Technology Systems 188

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 159

Big Data Government Open Source Storage 159

DZone

DECEMBER 21, 2020

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. It is an open-source framework for distributed processing of large amounts of data.

Code 152

Code Java Big Data Open Source 152

DZone

JANUARY 20, 2023

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios.

Scalability 204

Scalability Big Data Hardware Internet 204

DZone

DECEMBER 21, 2020

Setting up a data warehouse is the first step towards fully utilizing big data analysis. Still, it is one of many that need to be taken before you can generate value from the data you gather. An important step in that chain of the process is data modeling and transformation.

Big Data 191

Big Data Google Scalability Processing 191

DZone

DECEMBER 28, 2020

Nowadays, Big Data tests mainly include data testing, paving the way for the Internet of Things to become the center point. Digital transformation is yet another significant focus point for the sectors and the enterprises that are ranking top on cloud and business analytics. Besides, AI and ML seem to reach a new level.

Software 187

Software Software Testing Big Data 187

Scalegrid

NOVEMBER 25, 2019

Google Cloud does offer their own wide column store and big data database called Bigtable which is actually ranked #111, one under ScyllaDB at #110 on DB-Engines. Google Cloud Platform (GCP) was the second most popular cloud provider for ScyllaDB, coming in at 30.4% of all cloud deployments.

Big Data 187

Big Data Database Open Source Azure 187

The Netflix TechBlog

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms.

Tuning 209

Tuning Efficiency Big Data Engineering 209

Dynatrace

JULY 6, 2022

This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation. Big data automation tools. These tools provide the means to collect, transfer, and process large volumes of data that are increasingly common in analytics applications.

Artificial Intelligence 185

Artificial Intelligence Tuning Strategy Big Data 185

The Netflix TechBlog

JUNE 20, 2024

To handle errors efficiently, Netflix developed a rule-based classifier for error classification called “Pensive.”

Data Engineering 198

Data Engineering Engineering Entertainment Software Engineering 198

Uber Engineering

JUNE 1, 2023

Uber runs more than 100K big data workloads per day using Apache Spark–at that scale it’s crucial to write optimized apps. The Delivery Data Solutions team built Spark Analysers, a real-time system to catch anti-patterns in the Spark application at Uber scale, helping Uber developers optimize their apps.

Big Data 77

Big Data Systems Development 77

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 146

Azure Cloud Big Data Virtualization 146

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Systems 109

Systems Big Data Storage Infrastructure 109

ScaleOut Software

JULY 19, 2021

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis.

IoT 78

IoT Analytics Big Data Architecture 78

The Netflix TechBlog

JUNE 1, 2021

clinical data was often small enough to fit into memory on an average computer and only in rare cases would its computation require any technical ingenuity or massive computing power. There was not enough scope to explore the distributed and large-scale computing challenges that usually come with big data processing.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130