Comparison of the Open Source OLAP Systems for Big Data: ClickHouse, Druid, and Pinot
In this post I want to compare ClickHouse, Druid, and Pinot, the three open source data stores that run analytical queries over big volumes of data with interactive latencies. Warning: this post is pretty big, you may want to read just the “Summary” section in the end. Sources of InformationI learned the implementation details of ClickHouse from Alexey Zatelepin, one of the core developers. The be
tim philip williams :: Functional pearl: Nested Datacubes
Introduction Multi-dimensional aggregation and grouping are common forms of analysis traditionally done with SQL databases, OLAP tools (Online Analytical Processing) and/or Excel pivot tables. These traditional tools use a flat table representation, whereby tuples are mapped to measures without any nesting. Increasingly, users are using general purpose programming languages for further offline ana
Cubrick: A Scalable Distributed MOLAP Database for Fast Analytics - Meta Research | Meta Research
Cubrick: A Scalable Distributed MOLAP Database for Fast Analytics41st International Conference on Very Large Databases (Ph.D Workshop) This paper describes the architecture and design of Cubrick, a distributed multidimensional in-memory database that enables real-time data analysis of large dynamic datasets. Cubrick has a strictly multidimensional data model composed of dimensions, dimensional hie
G-OLA: Generalized Online Aggregation for Interactive Analysis on Big Data
Nearly 15 years ago, Hellerstein, Haas and Wang proposed online aggregation (OLA), a technique that allows users to (1) observe the progress of a query by showing iteratively refined approximate answers, and (2) stop the query execution once its result achieves the desired accuracy. In this demonstration, we present G-OLA, a novel mini-batch execution model that generalizes OLA to support general
Open Sourcing Pinot: Scaling the Wall of Real-Time Analytics
Last fall we introduced Pinot, LinkedIn’s real-time analytics infrastructure, that we built to allow us to slice and dice across billions of rows in real-time across a wide variety of products. Today we are happy to announce that we have open sourced Pinot. We’ve had a lot of interest in Pinot and are excited to see how it is adopted by the open source community. We’ve been using it at LinkedIn fo
Announcing Kylin: Extreme OLAP Engine for Big Data
We are very excited to announce that eBay has released to the open-source community our distributed analytics engine: Kylin (http://kylin.io). Designed to accelerate analytics on Hadoop and allow the use of SQL-compatible tools, Kylin provides a SQL interface and multi-dimensional analysis (OLAP) on Hadoop to support extremely large datasets. Kylin is currently used in production by various busine
Workload Management for Big Data Analytics
Workload Management for Big Data Analytics Ashraf Aboulnaga University of Waterloo + Qatar Computing Research Institute Shivnath Babu Duke University Database Workloads On-line Airline Transactional Reservation Analytical OLAP Batch Payroll BI Report Generation This tutorial Different tuning for different workloads Different systems support different workloads Trend towards mixed work
Open Sourcing Cubert: A High Performance Computation Engine for Complex Big Data Analytics
Open Sourcing Cubert: A High Performance Computation Engine for Complex Big Data Analytics Authors: Maneesh Varshney, Srinivas Vemuri What do you do when your Hadoop ETL script is mercilessly killed because it is hogging too many resources on the cluster, or if it starts missing completion deadlines by hours? We encountered this exact same problem more than a year ago while building the computatio
Avatara: OLAP for Web-scale Analytics Products
We recently presented a paper about Avatara at VLDB 2012. Avatara is LinkedIn's scalable, low latency, and highly-available OLAP system for "sharded" multi-dimensional queries. It has been powering our analytical products, such as "Who's Viewed My Profile?" and "Who's Viewed This Job?", for two and a half years.Read less
Apache Kylin: OLAP Engine on Hadoop - Tech Deep Dive
Kylin is an open source Distributed Analytics Engine from eBay Inc. that provides SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets. If you want to do multi-dimension analysis on large data sets (billion+ rows) with low query latency (sub-seconds), Kylin is a good option. Kylin also provides seamless integration with existing BI tools (e.g Tableau).R
Apache Kylin | Analytical Data Warehouse for Big Data
Apache Kylin™ is an open source, distributed Analytical Data Warehouse for Big Data; it was designed to provide OLAP (Online Analytical Processing) capability in the big data era. By renovating the multi-dimensional cube and precalculation technology on Hadoop and Spark, Kylin is able to achieve near constant query speed regardless of the ever-growing data volume. Reducing query latency from minut
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WideTable: An Accelerator for Analytic Data Processing
http://pages.cs.wisc.edu/~jignesh/publ/WideTable.pdf
OLAP in Hadoop - Introduction ( Part 1 )
http://www.vldb.org/pvldb/vol8/p1716-goel.pdf
(PDF) Beyond basic faceted search
Graph cube: on warehousing and OLAP multidimensional networks
http://vldb.org/pvldb/vol5/p1874_liliwu_vldb2012.pdf
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