The latest trends and innovations in Big Data, IN-MEMORY COMPUTING, AND DISTRIBUTED SYSTEMS.

Analyzing Data in Ampool ADS using Apache Spark

Apache Spark is a distributed computing framework with implicit parallelism and fault-tolerance. The Ampool ADS is distributed in-memory store with built-in fault-tolerance. Typically Apache Spark caches data into its executor…

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MTable REST API

Continuing from our previous post on mutable tables, Introducing MTable, we now see how we can interact with this data abstraction through REST API's. The Ampool developer REST interface runs as an…

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Deep Dive with MTable

Continuing from the previous post , In this post we will demonstrate some of the APIs to create and access data in MTable. The example below uses Java APIs to create and…

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Introducing FTable

The previous post discussed about the mutable data in Ampool Active Data Store (ADS). Here we will discuss about how Ampool ADS enables you to deal with very large volume…

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Introducing MTable

Continuing from the previous post, we now introduce MTable, one of the mechanisms to store/Query/Scan data from Ampool's Active Data Store (ADS). MTable stands for mutable table. In subsequent posts we will learn…

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Introducing Ampool Tables

As mentioned in previous posts, Ampool is a memory-centric, data aware, distributed store which extends the proven open source Apache Geode project to support multiple types of application workloads. Apache…

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