Why Knowi is Different

The plethora of tools required to cobble the data stack together has not lived up to its hype on driving business value. Knowi is a rethink of the whole process from raw data to business user insights.

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Elasticsearch Native Integration, Reporting and Visualization​

Cloud or On-premise Deployments
Plugin Elasticsearch Queries
Schema Discovery & Elasticsearch Query Generation
Join and blend data across various NoSQL and SQL based datasources
Direct query execution into your database to drive visualizations, or, store and track seamlessly using our scalable, schema-less, flexible cloud warehouse
Prediction algorithms that auto-selects the best prediction models and forecast for any dataset
Plug-in architecture for custom logic & custom prediction algorithms
Incremental data pulls and warehouse updates
Push API to send real-time data
Data Export API
Single Sign-On API for embedding inside your portal
Interactive filters
Drilldowns
Choose from 40+ visualization options
AI powered Analytics
Share and embed dashbaords
Works on any device

📆 Book your 30 minute demo

Elasticsearch Analytics Features

Native Elasticsearch analytics

You simply connect Knowi to Elasticsearch and start writing queries. Knowi is the only complete BI solution that is fully native to Elasticsearch and supports nested objects and arrays. No ODBC drivers, no SQL layer in the middle, no pre-defined schemas, no ETL. No mess. No fuss.

Cross database joins

Join Elasticsearch data with NoSQL, Relational, RDBMS, and APIs on the fly across data centers or multiple cloud providers, eliminating costly ETL processes that move and SQL-ify your MongoDB data.

Search-based analytics

Transform how your company uses its data with the use of Google-search-like capabilities on top of Elasticsearch. Knowi’s search-based analytics will enable your business users to perform ad-hoc analysis in real time.

Embedded Mongo Database Analytics

Build Data-Driven Applications: With just a few clicks, you can securely embed dashboards directly into your applications your business teams are already using. Users can also share Elasticsearch dashboards or email PDF reports to extend analytics reporting to offline users company wide.

Machine Learning

Combine hindsight and foresight with our machine learning workbench. Integrate machine learning directly into your Elasticsearch data analysis workflows. With Knowi ML, you can automatically trigger actions based on resulting calculations. You choose to integrate your custom algorithms or tap into our library of open source algorithms.

Triggers, Alerts, and Actions

Automate actions or notifications based on the results of your Elasticsearch analytics. Easily send notifications with data attached or invoke a webhook to initiate a process in a downstream application.

Kibana Alternative

One of the challenges companies face when using Elasticsearch for business intelligence is that Elasticsearch manages data in JSON documents and has no support for SQL. 

This means traditional BI tools like Power BI and Tableau don’t work with Elasticsearch without a lot of help. That help comes from development teams and massive engineering efforts to move Elasticsearch data into a relational database.

Kibana is a good solution for more technical users where a single Elasticsearch index is the only source of data for visualizations.

But how often does that happen these days? If you’re a typical company, you have a diverse data stack that includes Elasticsearch and a good number of other database technologies.

This is where Knowi comes in.

Unlike with Kibana dashboards, with Knowi you can visualize data across multiple indexes. You can dynamically blend data from other sources, like relational data stores or REST-APIs. And you can accelerate your Elasticsearch analytics projects by avoiding custom development.

Knowi natively supports SQL-style queries even when working with NoSQL datasources like Elasticsearch. So the problem of getting Elasticsearch to work with traditional BI tools is eliminated. 

How does Knowi compare with Kibana?

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  • Native Integration to Elasticsearch
  • Supports AWS Elasticsearch
  • Number of Supported Visualizations
  • Integrated Machine Learning
  • Share and Embedd Dashboards
  • Blend Across Indexes
  • Blend with Other NoSQL or Relational Data
  • Natural Language Queries

Knowi

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  • 30+
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Kibana

  • 17

Hundreds of companies trust Knowi to unify their analytics

Frequently Asked Questions

Some of our customers do deploy Knowi and Kibana together and use one or the other depending on the application. But the more common case is to use Knowi as a Kibana alternative. This is because it can duplicate the things Kibana does well, but can also do analytics with multiple databases and REST APIs.

Yes, Knowi can natively connect to AWS versions as well.

Yes. Although the Type field in Elasticsearch is being depreciated. So we would recommend another approach.

Not sure how to move on from the Type field? Send us an email to support@knowi.com. We would love to help you come up with a solution.

Need to scale beyond Kibana for Elastic Analytics?​

Why Knowi?

In this blog post, Knowi’s very own Head of Solutions Engineering Shaun Leach, recounts his career journey towards Knowi, describes the challenges in the Business Intelligence space, and why he’s excited about the role Knowi will play in its future.

So what do you look for when you’re considering your next job?

A lot of people are looking for a way to progress what they’ve already been doing and to bank on the skills they already have.

For me, it’s a little different. When I’m looking, it’s for an opportunity that’s exciting, that will actually make a difference and something that’s a paradigm shift from what people have already seen. It’s got to be something that I feel excited about and that is going to surprise people and really open people’s eyes to what’s possible in the world as you move forward!

So what did I look for and why Knowi?

For me, the biggest problem that needs to be addressed is getting data into the hands of business people. We do it at home all the while! We type our questions into a search bar and we get our answers immediately. This is what the world is like today! With all this power at our fingertips, we then come to work and we step back in time! If you want to know how many of a particular product has been sold in a specific region last week, how do you get your answer? You don’t have access to the data to be able to answer that question yourself so you have to pass it on to the BI team or the IT team, and then after being prioritised, it could be waiting 6,12 or even 18 months to get an answer to a question!

So, why is it a problem in the first place?

The normal process for creating insights on your data requires that you first take the data from the source system and transform the schema into something that is more digestible to the BI tools that are currently on the market. Once this has been done, the volumes are generally too large still for the BI tools, and the data then has to be aggregated and stored in another data store to be able to produce reports. At this, producing a report generally requires a very technical tool to create the visualisations that are eventually presented to the Business team, who asked the question in the first place. This still doesn’t provide real self-service.

The reality is, expecting business users to get up to speed with very technical BI tools and get an understanding of tables and schemas, and being able to bring data together from disparate sources is unrealistic. They don’t need to understand any of the technicalities. From their perspective there is specific language and vocabulary that they work with and they want to be able to use that to get an answer to their questions! Because of this, there are currently in the region of 3 million people in the world with a job title that is equivalent to Business Analyst or Data Analyst, in other words, people who create reports using BI tools. Contrast that with the nearly 3 billion people currently in the workforce! Even if you said less than a third of those would be in position to ask questions, that would still be in excess of 500 million people! This is why there is always a backlog! This is why you have to wait to get answers to questions. It’s just not scalable! Add to this the fact that 80% or more of the questions asked will be ad-hoc, so allowing business users to answer these questions themselves, rather than overloading the highly skilled and expensive BI resources, is critical to companies succeeding!

So, why Knowi?

When I looked at Knowi, it was a real lightbulb moment! For me, this was a significant step forward! This is something that changes the market and changes the way people are going to work. It ticked all the boxes of bringing all of the data sources together, whether from a SQL source, a NoSQL source, semi-structured data, API’s, data lakes etc, allowing joins across any of the data sources to get a correlated view across all the data sets, allowing you to access the data at source, or even provide the option to cache the data for ad-hoc use cases. It allows business logic transformations on the data, if required, and even gives the business users a real self-service tool, allowing natural language questions to access the data! Knowi effectively changes the way the BI can now be done, without having to use expensive and complex ETL tools, without the need to build Data Warehouses and Data Marts and being about to do away with the complex BI tools that block business users capability to answer their own questions!

That was something I wanted to be part of!

After all of this, if you want to see what got me so excited, come and talk to us, and see how your future could look for you…

Shaun Leach
Director of Solutions Engineering at Knowi

Unified Analytics for Modern Data

Blend SQL, NoSQL, and REST-API data together

Picto Modern Data Stack

Modern data present new challenges for analytics

Modern data stacks often include multiple databases, unstructured, semi-structured, or multi-structured data.

Despite rigorous data warehousing systems and complex ETL pipelines, one data source almost never has all the ansewrs.

Traditional BI tools were built for SQL data

Most business intelligence platforms today were originally designed for SQL data and do not work well with unstructured or semi-structured data. 

The result is that many companies have to move their flexible NoSQL data into a schema-based data warehouse before they can do analytics.

Comparison Chart 1
Knowi Architecture

We built Knowi to solve this problem

Knowi is built from the ground up on data virtualization; a technology that allows us to natively connect in to any data source and run analytics on that data in real-time. 

With Knowi, you can easily blend data from SQL and NoSQL data sources without first having to move everything to a relational database.

Ready to learn more about Knowi?

Datasets

Native Integration to Your Enterprise Data

We have the broadest native integration to NoSQL datasources along with SQL, REST-API, and JSON/CSV data. Simply select your datasource and configure the connection.

Your data stays in the source so there no ETL processes to build or ODBC drivers to install.

There are three connection options to meet your security needs. In all cases, your data stays put.

  • Our cloud to your cloud
  • SSH Tunnel
  • Using an agent

Frequently Asked Questions

Questions and answers about search-based analytics on Knowi

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A lot of business users have some data literacy but not the deep syntax knowledge required to analyze data themselves. With search-based analytics, your team (or customers if you embed) can explore the data by entering questions and getting back actionable data. This will eliminate the need to go to the data science team every time someone wants to explore the business metrics or statistics. 

In short, yes. And if you are employing a complex use case we recommend it. This usually involves working with the Knowi team of solution engineers to build out custom associations and synonyms for the natural language processing engine that powers your search-based analytics. 

Yes, the Knowi platform features full embedding with either iframes or javascript. It also features white-labeling so you can replace all Knowi branding with your own. With this option, you can let your clients enter queries in plain English and get back actionable data in real time.

Ready to empower your team with data?​