Blogs

14 Feb

How customers in Southeast Asia are adopting Open Source to scale up!

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Open source has come a long way since its nascent days in the late 80s. Technology stalwarts like IBM and Microsoft are embracing open source like never before. IBM’s acquisition of Red Hat for $34 billion or Microsoft’s acquisition of Citus Data very well prove that the open source game has upped. Open source has had a tremendous impact on the business world, owing to the cost advantages and agility that it provides in supporting business initiatives. Few of the reasons […]

Rekha Ramaswamy | Enterprise Sales Manager, Ashnik

14
Feb
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13 Feb

The Future Will Be Documented

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MongoDB was born out of frustration from using relational databases not designed for today’s modern applications. After 40 years of no real alternatives, we pioneered a new way to work with data – the MongoDB document model and the associated query language. Since MongoDB offered a profoundly different way of organizing data – something that was largely experimental at the time – we faced skepticism about the viability of the document model as a general purpose database, particularly for mission-critical workloads. […]

Rajiv Thapar | APAC Partner Director, MongoDB

13
Feb
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13 Feb

Open Source Software in the Enterprise Has Never Been Healthier

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Recently I spotted a study by Digital Ocean on the adoption of open source that found more than half of developers are contributing to open source projects. Looking at the media coverage, though, I was particularly struck by one headline that suggested employers were lukewarm to open source. The article picked up on one finding that only 25 per cent of employers would contribute more than $1,000 to open source projects. This completely misses the point. It fails to understand why enterprises engage with open […]

Ken Rugg | Chief Product and Strategy Officer, EDB

13
Feb
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13 Feb

Building a scalable architecture for Machine Data Analytics

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In this article, I am sharing an architecture on how to get insights from machine data and further analyse it. This architecture can act as an analytical platform for a scalable solution to analyse machine data. This article is divided into 2 parts. Part 1 describes the real-time processing of data using Spark and Elasticsearch. Part 2 describes the batch processing of data using Flume and HDFS. Problem Statement In the world of machine data, raw data does not provide any […]

Ayandeep Das | Technical Specialist - ETL, Ashnik

13
Feb
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13 Feb

Elastic Stack Sizing consideration and architecture

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We have recently completed a few challenging but successful implementations using the Elastic stack. One of the biggest challenges we came across is, ‘How one can size Elastic cluster?’. And my best response to this is – ‘It Depends’! Because there is no magic wand, there are many parameters to be considered. In this article I am sharing some of the considerations based on my experience of recent Elastic implementations. There are many factors which you need to consider while sizing […]

Ajit Gadge | Senior Database Consultant, Ashnik

13
Feb
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16 Jan

Everything you need to know about Connection Pooling in Postgres

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Connection pooling refers to the method of creating a pool of connections and caching those connections so that it can be reused again. PostgreSQL has a postmaster process, which spawns new processes for each new connection to the database. This process takes up around 2 to 3 MB memory which happens every time you create a connection to the database. Without connection pooling, for each connection, the postmaster process will have to spawn a new process at the back end using […]

Nikhil Shetty | Database Consultant, Ashnik

16
Jan
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