The purchase price of software is only a small proportion of the overall cost of owning software. The total cost of ownership (TCO) includes both direct and indirect costs: from software to implementation to resources required to operate (and maintain), and more.

The real investment starts the day that software gets installed. Founded by enterprise software veterans, BigID was built with this in mind: putting in place a number of innovations that ensure that the cost of deploying and owning BigID is far less than any other data discovery solution.

1. Agents vs Agentless

Agent-based architectures are typically hard to deploy, scale, and manage — and they’re expensive to instrument on endpoints. They can interfere with normal operation of a data source – introduce processing overhead – and are both time consuming and invasive to the operation of the underlying data source to upgrade.

BigID is built to run in a flexible, agentless microservices architecture: saving organizations resources — and enabling faster time-to-value so they can get more out of their data.

2: Microservice vs Client-server

Client-server is architecturally more complicated to install, scale laterally, ensure resilience, and update and upgrade.

BigID is a modern docker-kubernetes deployment. It can be run on bare linux or VM and is easy to configure, deploy, update, and run.

3: Cloud-native vs Legacy

Most data discovery tools on the market were designed in a different era when data centers predominated.

While BigID supports legacy and data center infrastructure, it can also be deployed natively in all the popular cloud infrastructures, from AWS to Azure to GCP to OpenShift.

4: Finding and Onboarding Data Stores

You can’t find dark and sensitive data unless you first know where to look. Even when you know what data stores to look inside, you may still miss shadow servers and data floating in data streams.

In order to be effective, traditional discovery tools require the enterprises to essentially have perfect knowledge of where their data stores reside — and what their sensitive data looks like — for their products to function.

BigID, on the other hand, provides multiple automations to find both the data stores themselves and the sensitive data inside those data stores. These include network, API and data stream discovery, intelligent CMDB integrations, ServiceNow workflows, cloud auto-discovery, and programmatic modules. Through integration with privileged identity management products, like CyberArk, Hashicorp, administrators don’t need to manually configure access for BigID scanners: reducing risk and saving time.

5: On-demand Scale

Traditional appliance or client-server data scanners require additional networking configuration to add lateral scale. BigID can dynamically spin up scanners to take on more load — or split scans into smaller units and subsequently decommission scanners when the need disappears.

6: Self-healing Scans

Traditional scanning tools aren’t able to handle errors or interruptions well, often freezing systems and scans.

BigID has developed a first-of-its-kind, self-healing scan that can automatically retry stalled scans. This complements native BigID controls for stopping, suspending, starting, splitting, and resuming scans based on automated triggers or manual intervention.

7: Scheduling Your Way

Most data discovery tools still rely on manual starts or primitive schedule management to order when scans are to happen. BigID provides a range of options to easily adapt scan management to a company’s operational preferences.

With BigID, scans can be started, stopped, suspended, and resumed manually or automatically based on specific events — and targeted data sources or groups of data sources can be scheduled for specific times or specific time windows. Scans can be automatically initiated based on availability information from popular APM tools as well. They can be iterative, split, or sequenced — and initiated on changes like new file or changed schema. For ephemeral data sources, scans can also be started dynamically based on data creation events.

8: Fast, Stateless Updates

Software updates in enterprise environments are typically complicated, time consuming affairs that may involve downtime. For older appliance, agent, or client-server based systems, this is unavoidable. For these older systems, updates are typically done once or twice a year (at best), limiting how quickly new functionality can be introduced into production. Meanwhile, upgrades have to be done in a specific sequence, requiring intermediate upgrades to get to the functionality that a company wants.

BigID changes all this. BigID software updates are released on a two-week rolling agile schedule. Customers can update whenever and wherever they like without taking anything down or backing anything up. Everything is done with a single command line — and configurations are preserved between updates.

9. Extensibility and Future-proofing

Nothing frustrates enterprises more than software that can’t be extended to interoperate with their existing tools, or solutions that are unable to evolve with their changing needs and priorities.

BigID was designed API-first so that enterprises can easily leverage additional integrations and orchestrations. Frequently used integrations include ServiceNow, SAP, RSA, Microsoft, CyberArk, Hashicorp, Salesforce, Okta, Alation, Collibra, ASG, IBM, Elastic, and Tableau.

BigID’s App Framework and App Marketplace further extend the scalability of BigID – by empowering customers and partners to get more value from their data by building custom application functionality on top of the BigID data discovery foundation.

In addition, BigID is the first vendor in the data discovery landscape with a full app marketplace for add-on apps, along with an SDK for building add-on functionality by a customer or partner.

10. Developer Orientation

As more and more companies shift left, there is growing desire for companies to provision capabilities like data discovery, data privacy, data protection, and data perspectives as part of a CI/CD development process.

BigID is the first and only data discovery tool that can be instrumented and operated as part of a developer build process.

11. Hidden Dependencies

Batteries should always be included. Nevertheless, many products require additional products like a Hadoop cluster to function.

BigID has everything needed, pre-installed and ready to go. You can extend and integrate as necessary — for something like a preferred case management system, for example — but nothing additional is required to get the most out of BigID. Everything is included.

12. Infrastructure Demands

Some data discovery products require installation of heavy appliances or require large compute infrastructure to support functionality.

BigID optimizes and distributes workloads and does not copy data — ensuring a more modest infrastructure demand relative to other data discovery tools.

13. Performance

While most discovery technologies today depend on adding additional compute resources for underlying speed increases, BigID uses advanced intelligent analysis to optimize different kinds of computational operations like classification, cataloging, cluster analysis, correlation, or data subject rights fulfillment.

From efficient server deployment to optimized scanning, workflow enablement to seamless updates, extensibility to scalability, BigID takes every implementation and integration concern into consideration — keeping innovation for your company top of mind.

Upgrading to an inherently modern platform that was designed to not only reduce indirect costs, but simplify and streamline processes every step of the way, reduces the TCO of software ownership in ways that no other discovery solution can.

Check out a quick overview of BigID’s data intelligence platform – or set up a 1:1 demo to see how BigID fits in your environment.