Looker vs Sisense: 6 Critical Differences

Aakash Raman • Last Modified: December 29th, 2022

In the popular field of Data Analytics and Business Intelligence, many companies are emerging with newer products, tools & features with respect to the way they deliver solutions to their customers and gather insights from their data. With such a diverse field gaining popularity day by day, it is common for companies in this field to try new techniques to improve upon their products and services to occupy the majority of customer share. When it comes to the field of Business Intelligence, the choice of Looker vs Sisense is a relatively tough one.

Looker is a Cloud-based BI tool that was acquired by Google in 2019 and is now a part of the Google Cloud Platform. It supports multiple data sources and manages the process of Data Visualization efficiently, according to your business requirements. It also helps you monitor the performance of your Sales, Advertisement campaigns, Business operations, and a lot more. Sisense is a popular AI-driven, BI software company that focuses on providing analytical solutions for all its customers, helping them go beyond the traditional dashboard and efficiently visualize their data. 

This article provides you with a comprehensive analysis of both BI tools and highlights the major differences between them to help you make the Looker vs Sisense decision with ease. It also provides you a brief overview of both BI tools along with their features. Finally, it highlights a few challenges you might face when you use these BI tools. Read along to find out how you can choose the right BI tool for your organization.

Table of Contents

Introduction to Looker

Looker Logo
Image Source

Looker is a Cloud-based BI tool and computer software company that helps businesses enhance their overall outlook and intelligence by providing smarter data-driven insights from multiple data sources. It was founded by Llyod Tabb and Ben Porterfield in 2012 and its current headquarters are in Santa Cruz, California. It was acquired by Google in 2019 and is now part of the Google Cloud Platform. Looker supports multiple data sources and deployment methods so that you can leverage them for all your analytical needs without compromising the transparency, security, or privacy of your data.

Key Features of Looker

Looker houses a wide range of features that differentiates it from the other BI tools. Some of those features are given below:

  • Looker helps you create real-time dashboards for an in-depth and consistent analysis of your data.
  • It helps you integrate multiple tools and amplify their capabilities when analyzing data so that you can make better data-driven decisions.
  • It makes all your workflows data-driven by regenerating them with fresh, and reliable data. Looker gives teams unified access to the answers they need to drive successful outcomes.
  • Looker also helps you build custom applications to interact with your customers easily.
  • It can also help establish a live connection with any SQL database on any infrastructure.

The architecture of Looker is shown below.

Looker vs Sisense: Looker Architecture
Image Source

To learn more about Looker, click this link.

Introduction to Sisense

Sisense Logo
Image Source

Sisense is a Business-Intelligence, AI-driven software company founded in 2004 by Elad Israeli, Eldad Farkash, Aviad Harell, Guy Boyangu, and Adi Azaria. Its headquarters are located in New York City, New York. The main goal of Sisense is to provide APIs for customizations and building personalized analytic experiences for any application.

Key Features of Sisense

Sisense houses a wide range of features that make it a popular option over other BI tools. Some of those features are:

  • Sisense helps perform a detailed ad-hoc analysis of highly voluminous data. It effectively handles data on the scale using a single commodity server.
  • It solves complex business queries without programming or SQL querying and unifies data.
  • It offers a wide range of widgets such as charts, gauges, and graphs and, allowing you to embed entire dashboards or individual widgets.
  • It integrates seamlessly with web portals, external websites, and web applications.
  • It has a centralized data hub and has interactive browser-based dashboards. It also supports data exports in CSV, PDF, Excel, and many other formats.
  • It consolidates, stores, and accumulates data using an intuitive script-less user interface.

The architecture of Sisense is shown below.

Sisense Architecture
Image Source

To learn more about Sisense, click this link.

Simplify Data Analysis with Hevo’s No-code Data Pipeline

Hevo Data, a No-code Data Pipeline helps to load data from any data source such as Databases, SaaS applications, Cloud Storage, SDK,s, and Streaming Services and simplifies the ETL process. It supports Looker and Sisense, along with 100+ data sources (including 30+ free data sources), and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. Hevo not only loads the data onto the desired Data Warehouse/destination but also enriches the data and transforms it into an analysis-ready form without having to write a single line of code.

Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different BI tools as well.

Check out why Hevo is the Best:

  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
  • Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  • Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
  • Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
  • Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.

Simplify your Data Analysis with Hevo today! Sign up here for a 14-day free trial!

Factors that Drive the Looker vs Sisense Decision

Now that you have a basic idea of both technologies, let us attempt to answer the Looker vs Sisense question. There is no one-size-fits-all answer here and the decision has to be taken based on the business requirements, budget, and parameters listed below. The following are the key factors that drive the Looker Sisense comparison:

1) Looker vs Sisense: Data Governance

Data Governance is the process of managing the availability, usability, integrity, and security of data in an enterprise environment.

Looker enforces Data Governance by ensuring that the data your business leverages to make decisions are effective, efficient, secure, and private. It improves your Data Quality by organizing the collection and storage of your data in a systematic and orderly manner. It also incorporates any updates and modifications made when data is extracted or transformed.

Sisense incorporates Data Governance by monitoring the actions of 5 main users: Administrator, Data Administrator, Designer, Data Designer, and Viewer. Each of these roles comes with default settings and access configurations. By using the Sisense API, administrators have granular control over the permissions of each role.

2) Looker vs Sisense: Embedded & Advanced Analytics

Embedded Analytics is the technology that makes Data Analysis and Business Intelligence more accessible for any application or user. As both BI tools offer Embedded Analytics, it is important to understand what features each tool offers towards this.

Looker offers Embedded Analytics on its platform. It helps you create intelligent, dynamic, and faster applications while maintaining a constant user-friendly interface. This way you can create systematic workflows, thereby generating more revenue and reducing developmental costs too.

Sisense offers Embedded Analytics and a platform to develop applications. You can use Embedded Analytics in Sisense and link them to existing applications via iframes, JavaScript APIs, or Plugins. You can also build your applications in Sisense by using BIoX, a visual template tool that supports customization capabilities via CSS and JSON. Sisense further houses support for integration with Amazon Alexa and many other IoT (Internet of Things) bots and tools.

3) Looker vs Sisense: Power & Performance

Processing Power determines how effectively a tool can process data. The processing power is an important factor when choosing a BI tool as it measures the efficiency of the tool to extract valuable insights from multiple data sources.

Looker operates as a program that runs on a server. It uses the memory and the CPU of the server to run. Companies that use Looker, group multiple servers and form clusters to provide the processing power for Looker to analyze that data. When you log into Looker from your browser, the browser sends requests to the server/cluster of your company for information. The server returns the desired information and your browser renders it for you. Looker automatically connects with your database too.

Sisense uses in-chip technology to process data. This means that it leverages the computer’s CPU to its full extent and this processor-based computing works much faster than tasks that run on the RAM and the disk memory. In-chip technology divides all queries into blocks so that the processor can access and reuse them in future queries. The more queries you make, the more blocks you have, and the faster Sisense can access the data in subsequent queries. This improves concurrent processing and also supports parallelism in tasks.

4) Looker vs Sisense: Additional Features

Both Sisense and Tableau offer Additional Features based on Natural Language that produce narratives to explain your user’s data. 

Looker enforces Natural Language Features by using Keboola, Looker’s NLP (Natural Language Processing) block. Keboola effectively understands the voice of your customers and gives you a detailed overview of your ratings and reviews, customers’ top topics, and a quick view of issues and opportunities for all your customers.

Sisense leverages the Sisense Narratives License to add Natural Language to its application. By using this feature, Sisense incorporates English descriptions to individual widgets that provide context. Sisense also offers Boto, a natural language bot that companies can use in third-party apps like Slack, Skype, or Facebook. Users can ask Boto a question, and Boto will analyze data and return a Natural Language answer. 

5) Looker vs Sisense: Connectors

Both BI tools offer a wide range of BI platform implementations that help the process, store and visualize data from multiple data sources and connections. As each tool offers support for different data sources, proper procedures must be put in place to import the data.

Looker offers connectors on the Cloud as it needs a server to run. Importing data is pretty simple and is completed within a matter of minutes using the Looker UI. Looker uses Looker Blocks, Looker’s pre-built data model, and dashboard to help you gain holistic insights from your data. Data Visualization can then be performed by using the flexible Looker Modelling Layer.

Sisense offers database connections on its premises and on the Cloud. The import process is relatively simple and can be established with few IT resources/infrastructure as well. However, users must have a strong knowledge of SQL to import tables, spreadsheets, and data formatting techniques. Connections are established using Elasticube tools that import data directly into Sisense. Connections can also be made using third-party applications but cannot be saved on Sisense.

6) Looker vs Sisense: Pricing Models & Deployment

Both BI tools offer a flexible and simple pricing model and deployment. They consider the needs of their customers and whether their deployment is On-Premise or on the Cloud.

Looker can be deployed by installing & configuring it with your data source and adding authentication and authorization policies to secure the connection. Deployment of Lookerhosted instances has historically been on Looker’s Virtual Private Cloud (VPC) on Amazon Web Service (AWS).

The pricing model of Looker is dynamic as its prices are based on the type of business you operate on. Companies that want to use Looker need to have a meeting with Looker’s employees. The pricing model of Looker is shown below.

Looker's Pricing Model
Image Source: Self

Sisense follows a hybrid deployment method and is available both on the Cloud and On-Premise. Pricing follows a pay-as-you-go model and additional features such as embedded analytics and natural language narratives increase the default amount.

The pricing model of Sisense follows a transparent and flexible approach with a ‘no-surprise’ workflow. Companies that want to use Sisense need to have a meeting with Sisense’s employees. The pricing model of Sisense is shown below.

Sisense's Pricing Model
Image Source: Self

Challenges of Looker

Now that you have a good idea about Looker, it is now important to understand some of the challenges you might encounter while working with Looker. The challenges of Looker are:

  • The creation of Data Silos is still a problem in many Data Visualization tools like Looker.
  • In some cases, data does not become business-ready for analysis.
  • Looker dashboards are dependent on your network requirements as they are loaded by the server.

Challenges of Sisense

Now that you have a good idea about Sisense, it is now important to understand some of its challenges. The challenges of Sisense are:

  • Users need to have a strong technical knowledge of BI to understand the Sisense dashboard.
  • There are no advanced graphics available to create detailed visualizations or a plain default format to create simple visualizations in Sisense.
  • The Elasticube functionalities are time-consuming and prone to errors.

Conclusion

This article gave a comprehensive analysis of the 2 popular BI tools in the market today: Looker vs Sisense. It talks about both BI tools and, their features and limitations. It also gave the parameters to judge each of the BI tools. Overall, the Looker vs Sisense choice solely depends on the goal of the company and the resources it has.

Looker is a good choice if all your data sources are stored in the Cloud. As your data sources are on the Cloud, you can install Looker and integrate them almost instantly. Similarly, if you have excellent network and storage options available, Looker is the best choice for you. Sisense will be a good choice if your team has prioritized the building of analytical applications and has multiple tools integrated into those applications.

In case you want to integrate data from data sources like Looker and Sisense into your desired Database/destination and seamlessly visualize it in a BI tool of your choice, then Hevo Data is the right choice for you! It will help simplify the ETL and management process of both the data sources and destinations.

Want to take Hevo for a spin? Sign up here for a 14-day free trial and experience the feature-rich Hevo suite first hand.

Share your experience of learning about Looker vs Sisense in the comments section below.

No-code Data Pipeline For your Data Warehouse