Ahana Cloud for Presto is a SaaS Managed Service which speeds up the performance of leading business intelligence, data visualization, and SQL tools like Qlik.
Faster data visualizations & interactive, ad hoc queries for Qlik
What is Qlik? Qlik is a platform providing data visualization and BI for end-to-end analysis of data. It offers interactive and user-customizable data visualizations, data federations, data analytics, and business intelligence (BI). Qlik enables its users to use data from different sources to carry out interactive data analysis and visualization. Organizations can leverage the available data for day-to-day decision-making and daily operational processes, promoting a data-driven culture. Some of the companies using Qlik include Samsung, Toyota, HSBC, Merck, and Shell.
Qlik comes in two versions, a Windows application and a cloud offering. Qlik can also be deployed on multiple cloud environments. It provides an association between data that could potentially reside in different data sources and carrying out analytics in-memory for improved performance. This provides fast analytics and a unified view of an organization’s data.
The Architecture of a Qlik App
A Qlik app consists of data source, back-end, and front-end components. The data source end is responsible for handling data access between the app the various data sources used. The back-end component container contains the Publisher which is responsible for pulling data from the different sources and providing the view files to a Qlik Server. It is mainly used by software developers, system analysts, database administrators, and other tech personnel.
The front-end accesses the views provided by the server and presents it as an interactive web app. It leverages the associative model used by Qlik to make selections, the main way of carrying out data analysis. The main users are organizational employees in different departments including marketing, sales, finance, management, and logistics.
What Is Presto?
Presto is a SQL query engine originally developed by Facebook to replace Hive, enabling to quickly access the social media platform’s insights against huge amounts of data. It is meant to connect to different data sources and to perform queries against them in a parallel and distributed manner. Presto is an open source project, housed by The Linux Foundation’s Presto Foundation. The connector-based architecture allows disparate data sources like S3 cloud storage, relational, and NoSQL databases to be queried. Many hundreds of other companies have since adopted Presto including Uber, Twitter, Amazon, and Alibaba.
A Presto cluster consists of a single coordinator and several worker nodes. The worker nodes are responsible for connecting to various sources and transparently carrying out query processing in a distributed and parallel approach. The computational power of a cluster can thus be increased by increasing the number of worker nodes. This has made it a lightning-fast choice for organizations with different data formats and sources and/or a large amount of data to process.
Faster Queries and Unified Access to more Data using Qlik and Presto
By using Presto, an organization can create clusters running Qlik applications targeted at different use cases. These use cases include functions such as data aggregation, data analysis, ad-hoc querying, and data visualization. It also helps an organization develop a unified view of the data. Qlik apps only have to interface with one data service, Presto, while being able to query multiple data sources. This is because Presto abstracts the different data sources being used by the apps.
The common approach is to deploy different Presto clusters for different use cases. The Qlik apps then connect to the clusters, relying on the clusters to perform actual data querying. Being an in-memory distributed query engine, PrestoDB can process large amounts in very short periods. The use of a cluster architecture means that horizontal scaling can be easily and efficiently carried out.
Combining Qlik and Presto enables organizations to create a highly scalable, distributed, and modern data engineering platform.
A typical architecture consists of Qlik connected to a presto cluster which, in turn, is connected to one or more data sources. Presto handles the data access and in-memory processing of queries. Qlik handles the visualization, reporting, and dashboarding. This allows the presto cluster to be scaled by adding or removing processing nodes to meet the workloads of the Qlik users. Integrating them offers other benefits such as data federation, fast query processing, and being able to have different clusters that can be optimized to best meet the needs of business analysts and data scientists.
Ahana Cloud is the cloud-native SaaS managed service for Presto, see how you can turbocharge Qlik in 30 minutes!