DocumentDB Analytics and Visualization Solutions
Which is the best DocumentDB analytics and visualization solution?
Table of Contents
3. Solutions Offering Native Integration
Introduction
Amazon DocumentDB is a fully managed NoSQL database service provided by AWS. It is used to store and query data as JSON-like documents. DocumentDB automatically scales compute and storage resources, saving users from worrying about the underlying infrastructure. It is highly scalable and flexible, suitable for use in mobile apps, content management, and real-time big data analytics.
Since it stores unstructured data, getting an analytics and visualization tool to pair with Amazon DocumentDB can be a challenge. In this article, we present some of the best analytics and visualization solutions for Amazon DocumentDB grouped in two categories.
Solutions Requiring a BI Connector
Tableau
Tableau is a powerful BI tool for data analysis and visualization that connects to Amazon DocumentDB through a BI connector. To connect Tableau to DocumentDB, you must download and install the Amazon DocumentDB JDBC driver and the DocumentDB Tableau connector. After a successful installation, the connector can be found under Tableau’s list of installed connectors. The connection requires you to provide the username and password for the DocumentDB database to connect to and other parameters such as the hostname, port, and database name. Authentication is done using your Amazon DocumentDB username and password.
Tableau Features
- Integrations
Tableau integrates natively with PDFs, files, spreadsheets, and SQL-based data sources. However, it lacks connectors to NoSQL data sources such as Amazon DocumentDB and Apache Cassandra. Users must depend on JDBC or ODBC connectors to connect to such sources.
2. Visualizations
Tableau has powerful, beautiful, customizable visualizations to help you present your DocumentDB data. Examples include charts, maps, stories, and dashboards.
3. Search-based Analytics
Tableau has the Ask Data feature to help users type questions about their data in a common language and get instant answers in the form of visualizations.
4. Cross-database Joins
Tableau supports joins across disparate data sources, allowing you to join your Amazon DocumentDB data with data from other sources. It supports inner join, left outer join, right outer join, and full outer join operations.
5. Embedded Analytics
Tableau users can embed their dashboards, visualizations, and analytical capabilities into external applications. The embedding can be done using a simple HTML embed code or Tableau’s JavaScript API.
6. Alerts/Anomaly Detection
With Tableau, you can configure alerts on views and dashboards to receive notifications when your data reaches certain thresholds. You can be notified via Slack, email, or within Tableau.
Benefits of Tableau
- Fit for non-technical users
Tableau’s Natural Language Processing capabilities enable non-technical users to understand their data by asking questions in a common language.
2. Beautiful visualizations
Tableau users can generate beautiful visualizations from their DocumentDB data.
Limitations of Tableau
- Complex integration
Integrating Tableau and Amazon DocumentDB is a lengthy, complex process. One has to download and configure the Amazon DocumentDB JDBC driver and the DocumentDB Tableau connector.
2. Legacy Architecture
Tableau users must depend on Tableau Desktop to publish workbooks to the Tableau Server or Cloud.
Power BI
Power BI is a BI tool created by Microsoft that supports integration with Amazon DocumentDB through a BI connector. It requires you to download and install the Amazon DocumentDB ODBC driver. Once installed correctly, the connector can be found under the “Get Data” tab in Power BI. The connector requires you to provide details such as the hostname, port, and the name of the Amazon DocumentDB database to connect to. Authentication is done using your Amazon DocumentDB username and password. Once connected to Amazon DocumentDB, Power BI users can import their data into the disk or run live queries against the database.
Power BI Features
- Integrations
Power BI comes with many software-as-a-service connectors to cloud data warehouses, SQL databases, and some NoSQL databases such as MongoDB.
2. Ask Questions of Your Data
Power BI has the Q&A feature for conversational analytics. You can ask questions about your Amazon DocumentDB data in natural language and get immediate answers in the form of charts and graphs.
3. Visualizations
Power BI offers many customizable visualizations to help you present your DocumentDB data. You can also create custom visualizations and share them with other Power BI users.
4. Embedded Analytics
Power BI allows users to embed reports, tiles, and dashboards in websites and web applications.
5. Alerts/Anomaly Detection
You can configure Power BI to notify you via email or within its notification center when your dashboard data changes beyond certain limits.
Benefits of Power BI
- Fit for non-technical users
Power BI’s Q&A feature allows non-technical users to understand their data by asking questions in natural language.
2. Customizable visualizations
Power BI users can edit or create custom visualizations to meet their unique needs.
Power BI Limitations
- Complex integration
Integrating Power BI with Amazon DocumentDB is a complex process. One has to download and correctly install the Amazon DocumentDB ODBC driver.
2. Bulky user interface
Power BI comes with a complex, bulky user interface. Users find it difficult to move from one component to another.
AWS QuickSight
AWS QuickSight is a cloud-native business intelligence tool that can be integrated with Amazon DocumentDB through a BI connector. To access your DocumentDB data from AWS QuickSight, you have to build an AWS Athena connector by creating a Lambda function on the AWS console with DocumentDB as the target database. You can then parse and query your DocumentDB data from Athena by customizing your SQL queries to transform the complex data types into simple data types. After building your query in Athena, you can point QuickSight to use it as the data source for generating visualizations.
AWS QuickSight Features
- Integrations
Amazon QuickSight supports native integration with relational data stores, files, JSON files, and software-as-a-service data sources.
2. Visualizations
QuickSight provides various visualizations for displaying data, including AutoGraphs, pie charts, and others.
3. Conversational Analytics
QuickSight supports conversational analytics through its Q feature powered by Natural Language Processing. Q extracts insights from data based on business questions.
4. Machine Learning
QuickSight has machine learning features to help you uncover insights from data, detect anomalies, and forecast business metrics. It also generates automatic narratives from your data.
5. Embedded Analytics
QuickSight users can embed analytics using the QuickSight API or dashboards by copying an embed code.
QuickSight Benefits
- Suitable for business users
QuickSight has Natural Language Processing capabilities, enabling it to uncover and deliver insights from business questions.
2. Fit for Advanced Analytics
QuickSight gives its users access to machine learning capabilities to perform advanced analytics.
Limitations of QuickSight
- Complex integration
To integrate QuickSight with DocumentDB, one has to build an Athena connector by writing a Lambda function on the AWS console. This is a complex process that requires technical knowledge.
2. Limited visualizations
QuickSight doesn’t have some of the necessary data visualizations.
Solutions Offering Native Integration
Knowi
Knowi is an AI-powered end-to-end analytics tool built for data stacks that store structured, unstructured, and multi-structured data. It provides the easiest integration with Amazon Document DB as it natively connects to DocumentDB without requiring you to install any driver or move your data to a relational structure. With Knowi, you can visualize your DocumentDB data, join it with data from relational, non-relational, and API sources, and start building dashboards in minutes. You can also take advantage of Knowi’s built-in AI capabilities to auto-generate dashboards, get insights, predict with machine learning, and ask questions of your data. They have also launched a new feature through which you can integrate your documents like PDFs with structured and unstructured data.
Knowi Features
- Data-as-a-Service
Knowi has a Data-as-a-Service feature that enables it to work with any type of data, whether structured or unstructured, small or big data. It natively connects to SQL, NoSQL, files, REST APIs, and cloud data sources. With Knowi, you can connect to Amazon DocumentDB without installing any driver.
2. Visualizations
Knowi gives you access to over 40 different types of customizable visualizations to present your DocumentDB data.
3. AI-powered Analytics
Knowi offers secure and transparent AI analytics that allows you to auto-generate dashboards, gain instant insights, utilize NLP for plain-English data queries, and deploy advanced machine learning models for predictions and actions.
4. Multi Data Source Joins
Knowi enables users to perform large-scale join operations involving multiple data sources on its user interface. You can join your DocumentDB data with data from NoSQL, SQL, files, REST APIs, and cloud data sources. Knowi supports inner join, right outer join, left outer join, full outer join, and loop join operations and they all depend on a common field across the data sources involved.
5. Embedded Analytics
Knowi users can generate a simple embed URL or a secure embed URL and use it to embed their dashboards, visualizations, or analytical capabilities into their applications. You can also use Single Sign-On embedding to prevent users signed into your applications from signing again into Knowi to view the embedded content.
6. Alerts/Anomaly Detection
Knowi sends real-time alerts to users to help them respond to changes that happen to their data or business. The alerts can be received via Slack, Webhook, email, or Microsoft Teams.
Knowi Benefits
- Fit for non-technical users
Knowi’s AI analytics capabilities enable non-technical users to understand their data by asking questions in plain English.
2. Customizable visualizations
Knowi users can edit their visualizations or create custom visualizations using CSS/JavaScript to meet their unique needs.
3. Fit for advanced analytics
Knowi comes with built-in machine learning algorithms to let users build models for advanced analytics.
Limitations of Knowi
- Complex user interface
Knowi has a simple user interface for business users. However, it has a complex user interface for data engineers, and it may take some time to get used to.
2. Visualizations are not very beautiful
Knowi doesn’t have the “prettiest” out-of-the-box visualizations. However, you can customize them using CSS/JavaScript.
Final Thoughts
Amazon DocumentDB is a fully managed, NoSQL database provided by AWS. Since it stores unstructured data, getting an analytics and visualization tool for your DocumentDB data can be a challenge.
Tableau, Power BI, and AWS QuickSight can provide analytics and visualization on DocumentDB data but require a BI connector.
Tableau requires you to download and install the Amazon DocumentDB JDBC driver and the DocumentDB Tableau connector to connect to DocumentDB.
Power BI requires you to download and install the Amazon DocumentDB ODBC driver to access your DocumentDB data.
To access Amazon DocumentDB from AWS QuickSight, you should build an AWS Athena connector by writing a Lambda function on the AWS console and setting Amazon DocumentDB as the target database.
However, with Knowi, an AI-powered Analytics tool, you can natively integrate with DocumentDB without requiring you to install any driver or move your data into a relational structure.
