Why Developers Choose Zen Edge Data Management?

digital transformation strategy

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DBTA Webinar Enabling Time-Series Analysis for Mobile and IoT

Why Developers Choose Zen Edge Data Management?


Edge applications and devices increasingly rely on AI to improve automation and decisions – human and machine – in stand-alone, peer-to-peer, local network, cloud and hybrid environments. The underlying edge data management must leverage a variety of hardware architectures, operating environments, networks, communications interfaces, and programming and scripting languages for applications that use these resources. Zen Edge Data Management delivers against these broad and demanding requirements.

Zen Edge Data Management Features

What Our Customers Are Saying

Friends don’t let friends use flat files

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Friends don’t let friends use flat files


ETL, data security, portability, indexing, time-stamping, and other features built-in to modern edge data management solutions no longer require a complex database that doesn’t fit your edge use case. With Zen you get the simplicity of file system APIs with the robust functionality of a real-time database.

Zen: Zero-DBA, Embedded, Nano-footprint, Multi-Model, Multi-Platform

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Zen: Zero-DBA, Embedded, Nano-footprint, Multi-Model, Multi-Platform


  • Single architecture – from device to gateway, from server to cloud
  • Multi-model, multi-platform, embedded in most popular languages
  • No ETL between clients, servers, and cloud
  • Modular: 7MB client to 50MB server to full enterprise under 200MB
  • AES 256-bit military-grade encryption
  • Embed in apps, configurable through APIs
  • Built-in automated defragmentation
  • Single data file/table size of 64 TB
HCL Compass

Today’s use cases demand more than SQLite.

Zen Editions

Zen Core

  • For mobile/IoT devices
  • Dedicated DB Engine with NoSQL API and SQL
  • Embeds directly in apps as packaged libraries
  • Client and Peer-to-Peer
  • 7 MB footprint
  • Royalty-free development and deployment

Zen Edge

  • Embed in Edge gateways and complex machinery
  • Full Client-Server functionality
  • >100s of concurrent users
  • 50MB footprint

Zen Enterprise

  • Zen Workgroup for Windows
  • Embed/bundle with ERP verticals, and other complex apps
  • >1000s of concurrent users for branch NS central office
  • 175MB footprint

Zen Cloud Server

  • Cloud-ready version of Zen Enterprise
  • Runs in VMs and Containers
  • Embed/bundle in complex SaaS apps or managed services

Shared by all Editions

  • Single modular architecture, code once, run anywhere
  • Zero ETL between Zen and PSQL ensures less integration and time to completion
  • SQL and NoSQL APIs
  • AES-256 bit encryption for data at rest plus zero ETL avoids decryption between development and deployment
  • Singe data table/file size maximum of 64 TB

Shared by all add-on software

  • Shared by all add-on software
  • API from CLI or embeds directly in your application
  • Windows 10 and Windows Server 2016 support
  • Embeddable APIs and configurable dashboards for remote management
HCL Compass

Upgrade from PSQL to Zen

Eight Indicators you need to modernize your Edge Data Management

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Eight Indicators you need to modernize your Edge Data Management


  • Do you need to analyze and make real-time decisions at the point of action?
  • Are you able to manage large sets of local and shared persistent data at the edge?
  • Do you need to run on multiple OSes from Android/iOS to Windows/Linux?
  • Do you use multiple programming and scripting languages to develop your edge applications?
  • Do you support varied types of data: JSON, Blob, traditional structured, etc.?
  • Are you struggling to support standalone, peer-to-peer, client-server, Internet/Intranet architectures?
  • Do you operate as stand-alone when disconnected?
  • Can you handle high-speed, multi-channel data collection and local machine learning inference?
If you’re struggling with any of these questions, you’re probably struggling with your Edge Data Management and need to modernize.

Embedded Database Management for IoT and Edge Environments

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Embedded Database Management for IoT and Edge Environments


Edge Intelligent applications need to embed sophisticated data management so developers don’t have to become database managers. Here’s some challenges, constraints, and issues to consider.

Zen Python demo for Facial Recognition on a Jetson board

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Zen Python demo for Facial Recognition on a Jetson board


On a Jeff Fritz podcast, Tom Bates from Actian describes how he used Open Source ML routines and cameras to do real-time facial recognition detection and Zen DB storage on a Jetson.