Blend Current and Historical Data
The Case for Shared Nothing
Shared-nothing has become the dominant parallel architecture for big data systems, such as MapReduce and Spark, analytics platforms, NoSQL databases and search engines [Özsu & Valduriez 2020]. The reason is […]
Blending Seamlessly Current & Historical Data: LeanXcale Bidimensional Partitioning
Motivation: Support Any Historical Monitoring Data Depth with High Efficiency One of the main tasks of a monitoring tool is to collect historical data. Tracking historical data allows companies to […]
Understanding Cluster Replication Scalability
Real Time KPIs
Understanding Cluster Replication Scalability
Cluster Replication and Logarithmic Scalability If you have been using cluster replication with some open source operational database, you might have noticed that they do not scale out well. If […]
Scalability
KPI Calculation: LeanXcale Online Aggregates
Motivation: Supporting High Data Ingestion Rates and Performing Frequent Aggregate Queries In real time analytics, a major requirement is to be able to ingest data at high rates, while at […]