BigQuery vs QlikView

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Our analysts compared BigQuery vs QlikView based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

QlikView Software Tool

Product Basics

BigQuery, a cloud-based data warehouse offered by Google, provides businesses with a scalable and cost-effective solution for analyzing massive datasets. It eliminates the need for infrastructure management, allowing users to focus on extracting valuable insights from their data using familiar SQL and built-in machine learning capabilities. BigQuery's serverless architecture enables efficient scaling, allowing you to query terabytes of data in seconds and petabytes in minutes.

BigQuery is particularly well-suited for organizations dealing with large and complex datasets that require rapid analysis. Its ability to integrate data from various sources, including Google Cloud Platform and other cloud providers, makes it a versatile tool for businesses with diverse data landscapes. Key benefits include scalability, ease of use, and cost-effectiveness. BigQuery offers a pay-as-you-go pricing model, allowing you to only pay for the resources you consume. You are billed based on the amount of data processed by your queries and the amount of data stored.

While BigQuery offers numerous advantages, it's important to consider factors such as your specific data analytics needs and budget when comparing it to similar products. User experiences with BigQuery have generally been positive, highlighting its speed, scalability, and ease of use. However, some users have noted that the pricing structure can become complex for highly demanding workloads.

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QlikView is a data discovery and customer insight platform from Qlik, a leader in the insight and intelligence space. However, it is not available for purchase any longer. Qlik Sense, Qlik’s next-generation offering, is available for new customers. It offers self-service data that can help drive decisions and generate significant ROI for technical skill level users.

It’s built from the ground up to be affordable, scalable and adaptable. It can ingest data from diverse sources like big data streams, file-based data, and on-premise or cloud data. It is well-known for its data associations and relationship functionality, keeping data in context automatically. It delivers results quickly via its patented in-memory data processing module, processing data down to as little as 10% of its original size.

Pros
  • Intuitive interface
  • Fast data visualization
  • Easy data exploration
  • User-friendly for non-technical users
  • Strong community and support
Cons
  • Limited data modeling capabilities
  • Licensing costs can be high
  • Customization can be challenging
  • Version control can be a concern
  • Performance can slow with large datasets
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$6.25/TiB, Usage-Based
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$2,500/User, Annual
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Product Assistance

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Live Online
Videos
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Email
Phone
Chat
FAQ
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Knowledge Base
24/7 Live Support
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24/7 Live Support

Product Insights

  • Forecast and Plan Ahead: Ingest large amounts of data quickly to strengthen forecasting and boost decision-making processes. 
  • Deliver Insights: Find discrepancies in data and act on them accordingly. 
  • Focus on Analytics and Not Infrastructure: Handles large volumes of data without putting strain on an organization’s IT resources. 
  • Provide a User-Friendly Environment: It’s user-friendly for both technical and non-technical users. High-level knowledge is not necessary to operate the software effectively. 
  • Speed Up Processes: Utilizes fast SQL databases to quickly and efficiently analyze terabytes worth of data. 
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  • Optimize Connections: Spot connections in data even when working with large data sets. Take a granular look at data through drill-down and view high-level trends in customer/employee behavior.
  • Increase Data Security and Control: Ensure total control over sensitive data. Prevent unauthorized access to crucial data sets through user-control, filtered views and permissions. AES-256 GCM provides data integrity and keeps information secured. Grant access to view data using user-specific access.
  • Enhance Functionality: Build the product in alignment with user needs and specifications. Extend functionality with QlikView Workbench to customize the app with custom scripting.
  • Increase Insight: Gain unparalleled insights into business operations, as well as the market at large. Track KPIs like sales, budgets, employee performance, and hundreds of other pre-built or custom data points.
  • Flexible Deployment: Choose from a cloud analytics solution, an on-premise installation, or a combined solution to get desired scalability and flexibility.
  • Intuitive Interface: Obtain data results via the self-service and code-free visual tool. Its accessible interface provides updated information instantly.
  • Empower Company Culture: Foster a data-driven culture by empowering employees to share data and insights directly or outside the platform.
  • Increase Competition: Monitor and track employee performance using KPI dashboards across organizations. Analyze changes in empirical data and make decisions to capitalize the profits.
  • Automated Recommendation: Receive and recommend automated context-aware suggestions using machine learning (ML). Prioritize recommendations on visualization type for easy access.
  • Accelerate Business Growth: Scale the businesses by deploying self-service and predictable BI. Test business performance using free tools available on the webpage.
  • Enhance Accessibility: Access all features from anywhere and on any device using an HTML5 client. Provides mobile push notifications to ensure unrestricted and consistent access.
  • Worldwide Support: Support fifteen languages and native currency conversions while detecting which language to use according to the browser or operating system.
  • Optimize Deployment and Configuration: Deploy quickly and allow for even quicker configuration because data is not required to be stored in any silos or cubes.
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  • Machine Learning: Comes with machine learning modules that can perform mass-segmentation and recommendations in seconds. These modules can be built and trained within minutes without ingesting data for training. 
  • Cloud Hosted: Handles all the hardware provisioning, warehousing and hardware management from the cloud. 
  • Real-Time Analytics: Large volumes of business data are quickly analyzed and presented to the user to ensure that insights and data discrepancies can be immediately uncovered. 
  • Automated Backups: Data is automatically stored and backed up multiple times a day. Data histories can be easily restored to prevent loss and major changes. 
  • Big Data Ecosystem Integrations: Integrate with other big data products such as Hadoop, Spark and Beam. Data can be directly written from the system into these products. 
  • Data Governance: Features such as access management, filter views, encryption and more are included in the software. The product is compliant with data regulations such as the GDPR. 
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  • Direct Data Source Connection: Connect to almost any data source, including cloud, big data, file-based and on-premise data. Pull information from many services (Salesforce, Hive, Teradata) and combine intel seamlessly into unique and intuitive dashboards.
  • Intelligent Visualization: Offer interactive displays and represent data in multiple ways for better data analysis. Flexible visualizations allow users to change and adjust graphics according to screen size.
  • Enterprise Collaboration: Facilitate collaboration for users to share the same dashboard, look at the same view or track one another as they navigate the application.
  • Strong Associations: Leverage the strength of the platform’s built-in association engine to conduct direct and indirect searches across data or within a single field. Identify data that is related and not associated.
  • Self-Service App Building: Build apps and files via the drag-and-drop function. Create individual lists with their visualization while managing and sharing across organizations.
  • Associative Indexing: Combine, transform and ingest data from multiple sources. Gathers data and indexes it to find logical associations. Explore and search big data repositories freely while keeping data intact.
  • Interactive Dashboards: Provide visualization capabilities and improve interaction using tooltip, lasso selection, filtering and drill-down functions. Encourage viewers to explore data by creating smart dashboards and distributing them using interactive elements.
  • In-Memory Application: House the software in memory, so conversions, queries and searches happen quicker and more efficiently. Eliminate problems that traditionally plague slow, on-disk applications. Locate all data in RAM.
  • Web Connectors: Extract data from multiple social networking sites and web-based sources using web APIs. Built-in connectors easily connect to any URL and fetch data.
  • Robust Data Controls: Enable meaningful data manipulation within the application by leveraging unique dashboards, reports and filter views.
  • Data Alerts: Spot anomalies and outliers by requesting context-aware alerts. Monitor and manage data without limitations.
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Product Ranking

#10

among all
Big Data Analytics Tools

#32

among all
Big Data Analytics Tools

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User Sentiment Summary

Excellent User Sentiment 724 reviews
Great User Sentiment 1859 reviews
90%
of users recommend this product

BigQuery has a 'excellent' User Satisfaction Rating of 90% when considering 724 user reviews from 3 recognized software review sites.

82%
of users recommend this product

QlikView has a 'great' User Satisfaction Rating of 82% when considering 1859 user reviews from 4 recognized software review sites.

4.4 (292)
4.1 (239)
n/a
4.3 (163)
4.6 (283)
4.2 (725)
4.4 (149)
3.9 (732)

Awards

BigQuery stands above the rest by achieving an ‘Excellent’ rating as a User Favorite.

User Favorite Award

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Synopsis of User Ratings and Reviews

Performance: The system can execute queries on massive amounts of data with agility, as specified by about 89% of users who mentioned performance.
Functionality: About 68% of users who reviewed functionality talked about its robust inbuilt features.
Ease of Use: The UI is simple and easy to navigate, according to about 72% of users who talked about user-friendliness.
Integration: Approximately 75% of reviewers who talked about integration said that it connects to numerous other tools seamlessly.
Scalability: All users who reviewed scalability said that the platform scales to thousands of servers.
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Data Visualization: Approximately 80% of users who review its data visualization capabilities are satisfied with its intuitive drag-and-drop feature, rich libraries and its range of aesthetically appealing data representation options.
Data Preparation: Of users who mention data processing, 83% appreciate the platform’s seemingly limitless data transformation capabilities that help them deep-dive into all possible data relationships to glean actionable insights.
Functionality: Among users who share their views on this platform, around 68% say that they are satisfied with the power of its associative query engine that enables faster on-the-fly calculations and analytics aggregation at the speed of thought.
Sharing and Collaboration: About 83% of users who comment on sharing capabilities appreciate its multi-tier permissions capabilities and easy sharing of reports with clients via external sharing options.
Setup: Around 66% of users who mention ease of setup say that QlikView has a fast implementation cycle.
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Cost: Approximately 76% of users who mentioned cost complained that it’s expensive, and charges can rack up quickly if queries aren’t properly constructed.
Learning Curve: About 82% of users mentioned that the software has a steep learning curve.
Resources: About 89% of users who spoke about resources said that documentation and video tutorials are lacking and need improvement.
Visualization: Data visualization capabilities aren’t up to the mark, according to all users who talked about visualization.
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Cost: Pricing plans are inflexible and can be cost-prohibitive for small organizations and startups, though large organizations may find that it offers high value, as stated by 93% of users who mention its cost.
Performance: Approximately 42% of users say that performance-wise, this platform is resource-hungry and liable to slow down when crunching large amounts of data on local machines.
User Interface and Graphics: Of users who mention user interface, around 44% say that it needs improvement in deep-dive capabilities, as well as its quality of graphics.
Reporting: Of users who mention reporting, approximately 46% say that it lacks ad-hoc reporting and built-in reporting capabilities, requiring paid plugins to enhance the graphics quality of reports.
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Bigquery is a scalable big data warehouse solution. It enables users to pull correlated data streams using SQL like queries. Queries are executed fast regardless of the size of the datasets. It manages the dynamic distribution of workloads across computational clusters. The easy-to-navigate UI is robust and allows the user to create and execute machine learning models seamlessly. Users liked that it can connect to a variety of data analytics and visualization tools. However, users complained that query optimization is an additional hassle they have to deal with, as the solution is expensive and poorly constructed queries can quickly accumulate charges. It can be overwhelming for the non-technical user, and SQL coding knowledge is required to leverage its data analysis capabilities. Data visualization features are lacking and in need of improvement.

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QlikView is one of the foremost BI solutions in the market today, mainly due to the power of its associative query engine to link data from multiple sources that drives its visually impressive dashboards. With its strong data visualization capabilities, users can perform search and filter through data on-the-fly and conduct deep-dives to glean insights that matter to them. With a fast setup, users can have their first data model up and running in very little time. The software resides in-memory and houses data in RAM for quicker retrieval. With multi-tier access permissions for in-organization users, it enables users to view executive summaries at a glance, while allowing them to drill-down into data to find out more. Sadly, Qlik is now scaling back on improvements and updates for QlikView and focusing on promoting QlikSense instead, a possible reason why its filter and search functions, ad-hoc reporting and graphics are lagging in terms of quality, as mentioned in many user reviews. Also, this platform can prove to be resource-heavy for databases housed on local machines, especially when performing batch update jobs. In addition to inflexible pricing plans and the cost of licensing, quite a few necessary add-ons are paid. In summary, QlikView is one of the leading in-memory BI tools available in the market today and rates excellently with users in terms of data aggregation and visualization capabilities; however, buyers should factor in its pricing plans and other limitations when searching for the perfect BI solution for their enterprise.

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