Introduction
Over the past decades, business intelligence tools have helped data analysts and business users to create dashboards and visualizations. This has facilitated data-driven decision-making in departments and executives to support company goals. However, to make use of a dashboard, it must be created first. One must pull in data, select and apply visualizations, and design the dashboard in a way that answers business questions. This can take hours or even days.
To overcome the above challenges, some business intelligence tools implemented the search-based analytics feature. Search-based analytics allows business users to ask questions in plain English and get answers in the form of actionable data and visualizations. This saves users from having to write SQL queries or create data visualizations manually.
ThoughtSpot, AWS Quicksight, and Knowi are some of the popular BI tools that support search-based analytics. ThoughtSpot was launched in 2012 while both AWS Quicksight and Knowi were released in 2015.
There are not many comparisons between these BI tools. We decided to do a 3-way comparison between ThoughtSpot vs AWS Quicksight vs Knowi to know where they stand with each other. Before getting into the comparison, let’s first do a brief overview of each BI tool.
ThoughtSpot
ThoughtSpot is a big data analytics and business intelligence platform that allows its users to explore, analyze, and share business analytics data easily and in real-time. The platform is powered by artificial intelligence which helps it to put the power of a thousand data analysts in the hands of a business person. ThoughtSpot allows you to extract insights from your data through search or a single click.
ThoughtSpot was founded in 2012 by Ajeet Singh, its CEO, and six other persons from Microsoft, Google, Oracle, and Amazon. The goal of the company is to push data analytics to “human scale” through search-driven data analytics.
AWS Quicksight
AWS Quicksight is a business intelligence platform from Amazon. The platform is powered by machine learning and it runs in the cloud. With AWS Quicksight, you can create dashboards and visualizations from your data for the people you work with, regardless of their geographic location. Such dashboards and visualizations can help business users to extract insights from data for decision-making. The dashboards and visualizations can also be embedded into websites, portals, and applications.
AWS Quicksight is also a scalable platform, scaling massively to support thousands of users without the need for additional infrastructure management.
The platform also integrates with many data sources. It was first announced at re:Invent 2015 with the goal of providing a faster and simple business intelligence tool.
Knowi
Knowi is a unified business intelligence platform that shortens the distance between raw data and evidence-based actions. It achieves this through its data virtualization feature which eliminates the need for taking data through the cumbersome ETL processes. This makes Knowi a unique BI platform from other BI tools like ThoughtSpot and AWS Quicksight. Knowi also has native integration with NoSQL data sources, allowing its users to analyze unstructured data directly, a feature not provided by traditional BI tools. Thus, Knowi users don’t have to go through the expensive and time-consuming steps needed to move data.
Knowi has a search-driven analytics feature powered by Natural Language processing. Its users can ask questions in English and get answers instantly. Knowi was launched in 2015 and today it’s the BI platform of choice to big enterprises in the world.
ThoughtSpot vs AWS Quicksight vs Knowi
In this section of the article, we will be discussing how ThoughtSpot vs AWS Quicksight vs Knowi compare to each other. The following core areas will be considered:
- Deployment
- User Friendliness
- Connectivity/Integration
- Visualizations
- Search-based Analytics
- Embedded Analytics
- Multi-source Joins
- Alerts/Anomaly Detection
- Machine Learning Algorithms
- Pricing
- Customer Support
Deployment
ThoughtSpot can be deployed as a cloud solution or as an on-premise appliance. All ThoughtSpot nodes must be on the same subnet and platform and connectivity should not be blocked between any two nodes.
AWS Quicksight was natively built for the cloud.
Knowi has a cloud-based as well as an on-premise version, that can be accessed via a web browser without support for desktop installations. It also provides its enterprise users with On-premise/Cloud/Hybrid deployment options.
User Friendliness
ThoughtSpot has a user-friendly user interface that makes it easy for beginners to search quickly and create visualizations on their own. However, it’s not so interactive.
AWS Quicksight has a modern and intuitive user interface for data discovery and visualization. This makes it a good BI tool even for beginners to data analytics.
Knowi has a simple, intuitive, and customizable user interface. However, its user interface for data engineers is sophisticated and may take some time for a user to get used to.
Hence, AWS Quicksight has the most intuitive user interface of the three BI tools.
Connectivity/Integration
ThoughtSpot provides the ThoughtSpot Loader (tsload) tool, which is a command-line tool for loading data from CSV files into a ThoughtSpot database schema. This is the most appropriate way of loading huge volumes of data into ThoughtSpot. You can also use this tool to script recurring data loads. ThoughtSpot also provides its users with certified clients, that is, JDBC and ODBC, for loading data from their ETL tools and other databases. ThoughtSpot users can also prepare their data in a spreadsheet and upload it through a user interface via its User Data Import feature. This feature allows ThoughtSpot users to load small volumes of data on their own. ThoughtSpot users can also connect the JDBC driver to Pentaho and use it to import data into ThoughtSpot.
Amazon Quicksight supports integration with a variety of data sources. The relational data stores that can be used as data sources in AWS Quicksight include Amazon Athena, Amazon Aurora, Amazon Redshift, Amazon OpenSearch Service 7.7 or later, Amazon Redshift Spectrum, Amazon S3 Analytics, Amazon S3, Apache Spark 2.0 or later, Exasol 7.1.2 or later, AWS IoT Analytics, MariaDB 10.0 or later, MySQL 5.1 or later, Oracle 12c or later, Microsoft SQL Server 2012 or later, PostgreSQL 9.3.1 or later, Snowflake, Teradata 14.0 or later, Timestream, and Presto 0.167 or later.
To access any additional data sources, you have to link them and import their data into the supported data sources. Amazon Athena databases, Amazon RDS instances, and Amazon Redshift clusters must be in AWS. The other database instances must be in Amazon EC2, On-premise/local database, or internet accessible environment to be accessible from AWS Quicksight.
Knowi supports integration with over 36 structured and unstructured data sources such as MongoDB, Elasticsearch, Apache Cassandra, and others.
Unlike other BI tools, Knowi supports native integration with NoSQL data sources. You can pull data from them without the need to rely on third-party drivers and “relationalize” the data. It uses a “data virtualization” feature to allow you to work with all types of data, whether structured or unstructured, small or big. Knowi also has a powerful REST API integration to connect to APIs and join data from different sources.
Thus, Knowi supports the highest number of integrations. Its ability to offer native integration with NoSQL data sources and work with unstructured data sets it apart from ThoughtSpot and AWS Quicksight.
Visualizations
ThoughtSpot supports different ways to visualize data. Its search-driven analytics feature gives users instant answers to their ad hoc queries returning insights in the form of automatic data visualizations.
The best chart depends on the nature of the user’s query. Some of the supported visualizations include column charts, bar charts, line charts, pie charts, scatter charts, bubble charts, funnel charts, heatmap, tables, and many others. Although ThoughtSpot automatically returns the best data visualization model, users are allowed to adjust the labels, axes, and chart types as they desire.
AWS Quicksight also offers a wide variety of visuals that you can use to display your data. Examples of these visualizations include box plots, bar charts, donut charts, filled maps, pivot tables, treemaps, word clouds, and more.
After creating a visualization, AWS Quicksight allows you to customize it to fit your needs. Some of the possible customizations include changing the type of visualization, applying filters, and sorting visual data. To create a visualization, you can select the data fields to be featured in the visualization and AutoGraph will let Amazon Quicksight determine the best type of visualization to use.
Knowi gives you access to over 30 different types of visualizations that you can use to display your data. You can add multiple visualizations to a single page to create a dashboard. Knowi also allows you to customize your dashboards and visualizations to meet your needs. If you are familiar with JavaScript, Knowi allows you to create custom visualizations to help you meet your specific needs.
Thus, unlike ThoughtSpot, AWS Quicksight and Knowi allow users to customize their visualizations to meet their specific needs. Knowi takes it a notch higher by allowing its users to create custom visualizations via JavaScript.
Search-based Analytics
ThoughtSpot has a search-based analytics feature to help its users get automated insights from their data. This feature allows ThoughtSpot users to analyze their data via search and generate reports and dashboards within seconds. The searches are translated into SQL and answers are calculated immediately.
AWS Quicksight has a search-based analytics feature known as Amazon Quicksight Q, which is powered by machine learning. However, this feature is only available to Quicksight enterprise edition users. With Q, Quicksights users can ask questions about their data in a natural language and get answers with relevant visualizations. Q also provides suggestions for business terms and phrases and does spell checks to save you from having to remember the exact terms in your data.
Knowi also has a powerful search-based analytics feature powered by Natural Language Processing (NLP). Knowi has also introduced this search-based analytics feature on Slack and Microsoft Teams, making it a unique BI tool in the market. The combination of Knowi’s search-based analytics feature with Slack and Microsoft Teams allows users to ask questions in a natural language like English directly from these apps and get instant answers. The answers can be in the form of data or visualizations.
Thus, Knowi has a clear edge on search-based analytics compared to ThoughtSpot and AWS Quicksight.
Embedded Analytics
ThoughtSpot supports embedded analytics, allowing you to embed your dashboards and visualizations to your business portal or application. You can also use this feature, to embed a search-driven experience and allow users to ask their own data questions. The feature also lets you embed liveboards to your apps to discover insights on the fly.
AWS Quicksight also allows its users to embed dashboards and visualizations into their applications. This feature uses a pay-per-use architecture, which means that you only pay when a user accesses the dashboards or reports. Its enterprise edition supports anonymous embedding, a feature that allows any reader to access your embedded reports and dashboards without provisioning.
Knowi comes with a number of options to support embedded analytics. You can generate a URL of your dashboard and embed it into your external applications. Knowi allows its users to create a secure URL that uses parameters to ensure that users only see the data they are supposed to see. It also provides the Single SignOn API that facilitates token exchange from users in your system to map to Knowi with user rights and permissions.
Multi-source Joins
ThoughtSpot supports four types of joins including INNER JOIN, LEFT OUTER JOIN, RIGHT OUTER JOIN, and FULL OUTER JOIN.
It allows you to choose a join type when creating or editing a join on the ThoughtSpot web interface. By default, ThoughtSpot uses the INNER JOIN type. However, ThoughtSpot requires data to be loaded into it and indexing needs to happen on top. This results in everything having to be held in memory, which drives up costs big time.
AWS Quicksight allows you to perform join operations on your data. Quicksight also supports cross-data joins to allow you to join data from different sources. However, the data sources must be supported by AWS Quicksight, including file-to-file, database-to-database, and file-to-database.
Knowi supports joins across multiple data sources to blend and store combined data. The join operations are performed based on a common field among the data sources.
Knowi supports INNER JOIN, LEFT OUTER JOIN, FULL OUTER JOIN, RIGHT OUTER JOIN, and LOOP JOIN. It uses the INNER JOIN as the default type of join operation. Knowi was designed to support large-scale join operations across millions of records over multiple data sources. It also provides its users with mechanisms to optimize the join operations for faster processing. Unlike ThoughtSpot, Knowi has the virtual dataset concept that doesn’t require the raw data loaded into it before performing joins.
Whereas ThoughtSpot supports join operations for the same data source, AWS Quicksight and Knowi support join operations across multiple data sources.
Alerts/Anomaly Detection
ThoughtSpot generates three types of notifications namely alerts, configuration events, and notification events.
Alerts show the time the alert was sent, the type of the alert, and the alert message. Configuration events notifications show any changes made to the system configuration. Notification events alerts send data load alerts to users, describing the user who did the action and the time the action was done. Users can also configure ThoughtSpot to receive the alerts on their email.
To stay updated on changes to your data, AWS Quicksight allows you to create threshold alerts. You can set thresholds for your data and be notified via email when the data crosses the thresholds. You can also view the alerts on any web browser supported by AWS Quicksight.
Knowi also has an alerts feature to help you stay on top of important changes that may occur to your data or business. This Knowi’s feature sends real-time notifications when particular conditions, thresholds, and anomalies are detected in your data. Knowi also allows its users to set up alerts directly on a widget based on a threshold, anomaly, or custom condition in the data. Users can receive the alerts via webhook, email, or Slack.
Machine Learning Algorithms
ThoughtSpot provides machine learning capabilities through its SpotIQ AI Engine. This engine uses insight-detection algorithms to find insights from data quickly. The engine uses the DataRank algorithm to learn what is most important to end users over time by collecting feedback from them. It helps to fine-tune the system for future use.
AWS Quicksight has a number of machine learning capabilities including anomaly detection, natural language narratives, contribution analysis, and forecasting. These make it easy for users to extract insights from data and make predictions.
Knowi comes with machine learning algorithms for performing tasks such as Classification, Regression Analysis, and Time-Series Anomaly Detection. Plans are underway to implement clustering and deep learning algorithms in Knowi.
Knowi also provides its users with a data preparation wizard to help them clean their data before doing supervised modeling activities. Knowi can also be integrated with third-party machine learning tools like Tensorflow and Amazon Sagemaker.
Pricing
ThoughtSpot has not provided pricing information on their website. To get detailed ThoughtSpot pricing information, contact the ThoughtSpot team. It offers two pricing plans namely ThoughtSpot Enterprise and ThoughtSpot Everywhere.
Both plans use a consumption or capacity-based licensing model in which the pricing depends on how an organization utilizes the ThoughtSpot product. The annual contract value for Thoughtspot is around $300k (from a few years ago). Thus, it’s pricey and requires a lot of hardware/compute resources.
AWS Quicksight has a two-tier pricing plan, Standard and Enterprise. Both plans provide Quicksight users with tools for creating and sharing data visualizations. However, the Standard edition doesn’t support Active Directory integration. The Enterprise edition supports two types of users namely Authors and Readers while the Standard edition only supports Authors. The Standard edition costs $9/month billed annually or $12/month if billed monthly. The Enterprise edition costs $18/user per month billed annually or $24/user per month if billed monthly.
Just like ThoughtSpot, Knowi has not made its pricing information publicly available. Instead, they have provided a form on their website that you can fill out to request pricing information. Knowi has three pricing plans namely Basic, Team, and Enterprise. Each plan comes with full onboarding and technical support. Knowi also offers discounts for startups and nonprofits. It doesn’t charge for email reports that require a user etc. in other systems.
The three BI platforms use different approaches to pricing. ThoughtSpot charges its users based on consumption. AWS Quicksight charges its users a fixed monthly or annual fee, and it’s the cheapest of the three BI tools. Knowi’s goal is to customize costs based on the needs of different users.
Customer Support
ThoughtSpot provides a variety of ways through which you can get help. They have created product documentation and videos to help you answer some of the questions that you may have. You can also ask a question on the ThoughtSpot community and get answers from other ThoughtSpot users.
ThoughtSpot allows you to contact and speak to their experts via phone during office hours. You can also contact the ThoughtSpot team by sending them an email or by filing a support ticket via their support portal.
AWS Quicksight provides extensive documentation to answer some of the questions that you may have. They also have a Knowledge Center that features the frequently asked questions by AWS customers and their answers. If you don’t get an answer to your question, you can check out the AWS Prescriptive guidance, AWS re:Post, or create a case from your AWS account to contact the AWS support team. However, you cannot contact the AWS support team via phone.
Knowi has a knowledge base where users type their questions and get answers in the form of articles. The user also gets the top article suggestions that may answer their question as they type.
Knowi also sends out release notes on the latest updates to the BI platform. They recently introduced a community forum with sourced questions and answers that may be of help to users. Knowi users can also submit tickets via its chat system powered by Zendesk and get answers to their questions.
ThoughtSpot vs AWS Quicksight vs Knowi – Final Thoughts
From the above discussion, each of the three BI tools comes with its own uniqueness. Each BI tool also has its own pros and cons.
ThoughtSpot is a good BI platform for any business looking for a search-powered data visualization tool for use even by business (non-technical) teams. It doesn’t support join operations from disparate data sources and uses a consumption-based pricing model.
If your business is looking for a BI platform with a moderate number of data visualization options and limited data integration options, choose AWS Quicksight. Quicksight will allow you to join data from multiple supported data sources. It also uses a fixed-price monthly or annual pricing scheme.
If your goal is to work with a BI platform with a flexible pricing plan and the ability to work with unstructured data, choose Knowi. Knowi will also let you connect to NoSQL data sources and shorten your journey from raw data to taking data-based actions. Though Knowi and AWS Quicksight were launched in the same year, Knowi has beaten ThoughtSpot in terms of features and provides a more modern approach to solving analytics problems.
