5 data integration trends that will define the future of ETL in 2018
ETL refers to extract, transform, load and it is generally used for data warehousing and data …
Kubernetes for Big Data Workloads
Kubernetes has emerged as go to container orchestration platform for data engineering teams. …
For next wave of innovation organisations will need internal data services
To unlock the true value of data, organisations will need internal data services. Data services …
Reflections on Apache Drill
I have been playing with Apache Drill for quite some time now. In layman’s terms, Apache Drill …
Rise of Elastic Data Warehouse and Database Services
Currently the majority of cloud based database and data warehouse services are provisioned with …
Requirements for stream processing architecture
In 2005 Stonebraker et al. published a paper that outlined 8 key requirements for stream processing …
Building Distributed Systems with Mesos
Apache Mesos is a popular open source cluster manager which enables building resource-efficient …
Hadoop Ecosystem- Deployment And Management
My notes and thoughts on Hadoop Ecosystem from book Hadoop Operations1. One of the major key take …
Traditional Ways To Solve Scalability Problems With RDBMS
Notes plus thoughts from my recent read Cassandra: The Definitive Guide. Common ways to solve …