Zoomdata is a modern microservices based platform that scales and offers a whole host of other benefits.
Microservices are loosely-coupled mini application servers that self-register with each other. Zoomdata microservices are written in Java.
Glad you asked! When done right, a platform built using microservices can be highly fault tolerant to maximize uptime and performance for mission-critical applications. Learn more about our journey towards simple scalability in this blog post: Microservices Architecture: A Brief History At Zoomdata.
Treating data as streams, rather than batches or sets, is fundamentally different from how traditional BI works. Zoomdata’s unique point of view that data can be represented in streams is baked into the web application, Query Engine, and Smart Data Connectors.
Zoomdata's streaming data analytics architecture uniquely supports:
Empower your whole organization to visualize and analyze streaming data for powerful real-time insights.
Work with data that's too big move using Zoomdata's unique Data Sharpening functionality.
Microqueries and Data Sharpening™ are patented technologies that work together to provide the most sophisticated end user experience for analyzing big data. There is literally nothing else like it available on the market today.
If enabled for a data source, the Query Engine determines whether to invoke microqueries. Microqueries repeatedly sample data across partitions and return the sample data to the Query Engine for processing.
Data Sharpening is the complementary process of analyzing sample data returned by microqueries, and streaming estimated results to the user’s browser (or other client). Data Sharpening’s estimated results may fluctuate a bit up or down until the final query resolves. However, the relative values of each group usually remain consistent as the data is sharpened. For example, the tallest bar in the chart at 10% completion will almost always remain the tallest bar at 100% completion. This means that users can be confident exploring data even as it streams live to the dashboard.
When the user zooms in, filters, changes metrics or groupings, or any other action that would change data values, Zoomdata cancels any active queries. Canceling active queries, however, is not trivial, and many JDBC drivers do not support it. In these cases, Zoomdata’s smart data connectors issue native API calls to complete the task.
No big data solution is complete without security. Our data architects have built security in to Zoomdata's architecture. Regardless of whether Zoomdata is used as a standalone BI platform or used to visually analyze data in an embedded application, it ensures adherence to the "three As" of security -- proper authentication, authorization, and auditing of the visual analytics environment.
Streaming architecture is fundamentally different from that used by traditional business intelligence (BI) systems. A streaming analytics architecture expects data to be in motion and flowing from the original source to the end user. Zoomdata is built for stream processing and consists of a set of data sources, the Zoomdata server, and clients that present visual analytics to end users.