What is Qlik and what are its top alternatives?
Top Alternatives to Qlik
- Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click. ...
- Power BI
It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. ...
- Looker
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way. ...
- QlikView
It is a business discovery platform that provides self-service BI for all business users in organizations. With this tool, you can analyze data and use your data discoveries to support decision making. ...
- Qlik Sense
It helps uncover insights that query-based BI tools simply miss. Our one-of-a-kind Associative Engine brings together all your data so users can freely search and explore to find new connections. AI and cognitive capabilities offer insight suggestions, automation and conversational interaction. ...
- Sisense
It is making business intelligence (BI) analytics easy with its simple drag-and-drop and scalable end-to-end BI processes that help to prepare, analyze, and visualize multiple complex datasets quickly. ...
- DOMO
Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform. ...
- Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. ...
Qlik alternatives & related posts
- Capable of visualising billions of rows6
- Intuitive and easy to learn1
- Responsive1
- Very expensive for small companies2
related Tableau posts
Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.
Hello everyone,
My team and I are currently in the process of selecting a Business Intelligence (BI) tool for our actively developing company, which has over 500 employees. We are considering open-source options.
We are keen to connect with a Head of Analytics or BI Analytics professional who has extensive experience working with any of these systems and is willing to share their insights. Ideally, we would like to speak with someone from companies that have transitioned from proprietary BI tools (such as PowerBI, Qlik, or Tableau) to open-source BI tools, or vice versa.
If you have any contacts or recommendations for individuals we could reach out to regarding this matter, we would greatly appreciate it. Additionally, if you are personally willing to share your experiences, please feel free to reach out to me directly. Thank you!
- Cross-filtering17
- Powerful Calculation Engine2
- Access from anywhere2
- Intuitive and complete internal ETL2
- Database visualisation2
- Azure Based Service1
related Power BI posts
Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.
Which among the two, Kyvos and Azure Analysis Services, should be used to build a Semantic Layer?
I have to build a Semantic Layer for the data warehouse platform and use Power BI for visualisation and the data lies in the Azure Managed Instance. I need to analyse the two platforms and find which suits best for the same.
- Real time in app customer chat support4
- GitHub integration4
- Reduces the barrier of entry to utilizing data1
- Price3
related Looker posts
We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.
related QlikView posts
related Qlik Sense posts
related Sisense posts
DOMO
related DOMO posts
- API for searching logs, running reports3
- Alert system based on custom query results3
- Dashboarding on any log contents2
- Custom log parsing as well as automatic parsing2
- Ability to style search results into reports2
- Query engine supports joining, aggregation, stats, etc2
- Splunk language supports string, date manip, math, etc2
- Rich GUI for searching live logs2
- Query any log as key-value pairs1
- Granular scheduling and time window support1
- Splunk query language rich so lots to learn1
related Splunk posts
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
We are currently exploring Elasticsearch and Splunk for our centralized logging solution. I need some feedback about these two tools. We expect our logs in the range of upwards > of 10TB of logging data.